NS2 PROJECT - ABSTRACTS
A Rank Correlation Based Detection against Distributed Reflection DoS Attacks DDoS presents a serious threat to the Internet since its inception, where lots of controlled hosts flood the victim site with massive packets.
Moreover, in Distributed Reflection DoS (DRDoS), attackers fool innocent servers (reflectors) into flushing packets to the victim. But most of current DRDoS detection mechanisms are associated with specific protocols and cannot be used for unknown protocols.
It is found that because of being stimulated by the same attacking flow, the responsive flows from reflectors have inherent relations: the packet rate of one converged responsive flow may have linear relationships with another. Based on this observation, the Rank Correlation based Detection (RCD) algorithm is proposed.
The preliminary simulations indicate that RCD can differentiate reflection flows from legitimate ones efficiently and effectively, thus can be used as a useable indicator for DRDoS.
A Resource Allocation Scheme for Scalable Video Multicast in WiMAX Relay Networks
This paper proposes the first resource allocation scheme in the literature to support scalable-video multicast for WiMAX relay networks.
We prove that when the available bandwidth is limited, the bandwidth allocation problems of 1) maximizing network throughput and 2) maximizing the number of satisfied users are NP-hard. To find the near-optimal solutions to this type of maximization problem in polynomial time, this study first proposes a greedy weighted algorithm, GWA, for bandwidth allocation. By incorporating table-consulting mechanisms, the proposed GWA can intelligently avoid redundant bandwidth allocation and thus accomplish high network performance (such as high network throughput or large number of satisfied users).
To maintain the high performance gained by GWA and simultaneously improve its worst case performance, this study extends GWA to a bounded version, BGWA, which guarantees that its performance gains are lower bounded.
This study shows that the computational complexity of BGWA is also in polynomial time and proves that BGWA can provide at least 1/ρ times the performance of the optimal solution, where \rho is a finite value no less than one. Finally, simulation results show that the proposed BGWA bandwidth allocation scheme can effectively achieve different performance objectives with different parameter settings.
Adaptive Position Update for Geographic Routing in Mobile Ad Hoc Networks
In geographic routing, nodes need to maintain up-to-date positions of their immediate neighbors for making effective forwarding decisions. Periodic broadcasting of beacon packets that contain the geographic location coordinates of the nodes is a popular method used by most geographic routing protocols to maintain neighbor positions.
We contend and demonstrate that periodic beaconing regardless of the node mobility and traffic patterns in the network is not attractive from both update cost and routing performance points of view. We propose the Adaptive Position Update (APU) strategy for geographic routing, which dynamically adjusts the frequency of position updates based on the mobility dynamics of the nodes and the forwarding patterns in the network.
APU is based on two simple principles: 1) nodes whose movements are harder to predict update their positions more frequently (and vice versa), and (ii) nodes closer to forwarding paths update their positions more frequently (and vice versa).
Our theoretical analysis, which is validated by NS2 simulations of a well-known geographic routing protocol, Greedy Perimeter Stateless Routing Protocol (GPSR), shows that APU can significantly reduce the update cost and improve the routing performance in terms of packet delivery ratio and average end-to-end delay in comparison with periodic beaconing and other recently proposed updating schemes.
The benefits of APU are further confirmed by undertaking evaluations in realistic network scenarios, which account for localization error, realistic radio propagation, and sparse network.
ALERT: An Anonymous Location-Based Efficient Routing Protocol in MANETs
Mobile Ad Hoc Networks (MANETs) use anonymous routing protocols that hide node identities and/or routes from outside observers in order to provide anonymity protection. However, existing anonymous routing protocols relying on either hop-by-hop encryption or redundant traffic, either generate high cost or cannot provide full anonymity protection to data sources, destinations, and routes.
The high cost exacerbates the inherent resource constraint problem in MANETs especially in multimedia wireless applications. To offer high anonymity protection at a low cost, we propose an Anonymous Location-based Efficient Routing proTocol (ALERT). ALERT dynamically partitions the network field into zones and randomly chooses nodes in zones as intermediate relay nodes, which form a nontraceable anonymous route. In addition, it hides the data initiator/receiver among many initiators/receivers to strengthen source and destination anonymity protection.
Thus, ALERT offers anonymity protection to sources, destinations, and routes. It also has strategies to effectively counter intersection and timing attacks. We theoretically analyze ALERT in terms of anonymity and efficiency.
Experimental results exhibit consistency with the theoretical analysis, and show that ALERT achieves better route anonymity protection and lower cost compared to other anonymous routing protocols. Also, ALERT achieves comparable routing efficiency to the GPSR geographical routing protocol.
The high cost exacerbates the inherent resource constraint problem in MANETs especially in multimedia wireless applications. To offer high anonymity protection at a low cost, we propose an Anonymous Location-based Efficient Routing proTocol (ALERT). ALERT dynamically partitions the network field into zones and randomly chooses nodes in zones as intermediate relay nodes, which form a nontraceable anonymous route. In addition, it hides the data initiator/receiver among many initiators/receivers to strengthen source and destination anonymity protection.
Thus, ALERT offers anonymity protection to sources, destinations, and routes. It also has strategies to effectively counter intersection and timing attacks. We theoretically analyze ALERT in terms of anonymity and efficiency.
Experimental results exhibit consistency with the theoretical analysis, and show that ALERT achieves better route anonymity protection and lower cost compared to other anonymous routing protocols. Also, ALERT achieves comparable routing efficiency to the GPSR geographical routing protocol.
An Efficient and Robust Addressing Protocol for Node Autoconfiguration in Ad Hoc Networks
Address assignment is a key challenge in ad hoc networks due to the lack of infrastructure. Autonomous addressing protocols require a distributed and self-managed mechanism to avoid address collisions in a dynamic network with fading channels, frequent partitions, and joining/leaving nodes.
We propose and analyze a lightweight protocol that configures mobile ad hoc nodes based on a distributed address database stored in filters that reduces the control load and makes the proposal robust to packet losses and network partitions.
We evaluate the performance of our protocol, considering joining nodes, partition merging events, and network initialization. Simulation results show that our protocol resolves all the address collisions and also reduces the control traffic when compared to previously proposed protocols.
We propose and analyze a lightweight protocol that configures mobile ad hoc nodes based on a distributed address database stored in filters that reduces the control load and makes the proposal robust to packet losses and network partitions.
We evaluate the performance of our protocol, considering joining nodes, partition merging events, and network initialization. Simulation results show that our protocol resolves all the address collisions and also reduces the control traffic when compared to previously proposed protocols.
Analysis of Distance-Based Location Management in Wireless Communication Networks
The performance of dynamic distance-based location management schemes (DBLMS) in wireless communication networks is analyzed. A Markov chain is developed as a mobility model to describe the movement of a mobile terminal in 2D cellular structures. The paging area residence time is characterized for arbitrary cell residence time by using the Markov chain. The expected number of paging area boundary crossings and the cost of the distance-based location update method are analyzed by using the classical renewal theory for two different call handling models.
For the call plus location update model, two cases are considered. In the first case, the intercall time has an arbitrary distribution and the cell residence time has an exponential distribution. In the second case, the intercall time has a hyper-Erlang distribution and the cell residence time has an arbitrary distribution.
the call without location update model, both intercall time and cell residence time can have arbitrary distributions. Our analysis makes it possible to find the optimal distance threshold that minimizes the total cost of location management in a DBLMS.
For the call plus location update model, two cases are considered. In the first case, the intercall time has an arbitrary distribution and the cell residence time has an exponential distribution. In the second case, the intercall time has a hyper-Erlang distribution and the cell residence time has an arbitrary distribution.
the call without location update model, both intercall time and cell residence time can have arbitrary distributions. Our analysis makes it possible to find the optimal distance threshold that minimizes the total cost of location management in a DBLMS.
Back-Pressure-Based Packet-by-Packet Adaptive Routing in Communication Networks
Back-pressure-based adaptive routing algorithms where each packet is routed along a possibly different path have been extensively studied in the literature. However, such algorithms typically result in poor delay performance and involve high implementation complexity. In this paper, we develop a new adaptive routing algorithm built upon the widely studied back-pressure algorithm.
We decouple the routing and scheduling components of the algorithm by designing a probabilistic routing table that is used to route packets to per-destination queues. The scheduling decisions in the case of wireless networks are made using counters called shadow queues.
The results are also extended to the case of networks that employ simple forms of network coding. In that case, our algorithm provides a low-complexity solution to optimally exploit the routing-coding tradeoff.
We decouple the routing and scheduling components of the algorithm by designing a probabilistic routing table that is used to route packets to per-destination queues. The scheduling decisions in the case of wireless networks are made using counters called shadow queues.
The results are also extended to the case of networks that employ simple forms of network coding. In that case, our algorithm provides a low-complexity solution to optimally exploit the routing-coding tradeoff.
BAHG: Back-Bone-Assisted Hop Greedy Routing for VANET's City Environments
Using advanced wireless local area network technologies, vehicular ad hoc networks (VANETs) have become viable and valuable for their wide variety of novel applications, such as road safety, multimedia content sharing, commerce on wheels, etc. Multihop information dissemination in VANETs is constrained by the high mobility of vehicles and the frequent disconnections.
Currently, geographic routing protocols are widely adopted for VANETs as they do not require route construction and route maintenance phases. Again, with connectivity awareness, they perform well in terms of reliable delivery. To obtain destination position, some protocols use flooding, which can be detrimental in city environments.
Further, in the case of sparse and void regions, frequent use of the recovery strategy elevates hop count. Some geographic routing protocols adopt the minimum weighted algorithm based on distance or connectivity to select intermediate intersections. However, the shortest path or the path with higher connectivity may include numerous intermediate intersections.
As a result, these protocols yield routing paths with higher hop count. In this paper, we propose a hop greedy routing scheme that yields a routing path with the minimum number of intermediate intersection nodes while taking connectivity into consideration. Moreover, we introduce back-bone nodes that play a key role in providing connectivity status around an intersection.
Apart from this, by tracking the movement of source as well as destination, the back-bone nodes enable a packet to be forwarded in the changed direction. Simulation results signify the benefits of the proposed routing strategy in terms of high packet delivery ratio and shorter end-to-end delay.
Currently, geographic routing protocols are widely adopted for VANETs as they do not require route construction and route maintenance phases. Again, with connectivity awareness, they perform well in terms of reliable delivery. To obtain destination position, some protocols use flooding, which can be detrimental in city environments.
Further, in the case of sparse and void regions, frequent use of the recovery strategy elevates hop count. Some geographic routing protocols adopt the minimum weighted algorithm based on distance or connectivity to select intermediate intersections. However, the shortest path or the path with higher connectivity may include numerous intermediate intersections.
As a result, these protocols yield routing paths with higher hop count. In this paper, we propose a hop greedy routing scheme that yields a routing path with the minimum number of intermediate intersection nodes while taking connectivity into consideration. Moreover, we introduce back-bone nodes that play a key role in providing connectivity status around an intersection.
Apart from this, by tracking the movement of source as well as destination, the back-bone nodes enable a packet to be forwarded in the changed direction. Simulation results signify the benefits of the proposed routing strategy in terms of high packet delivery ratio and shorter end-to-end delay.
Capacity of Hybrid Wireless Mesh Networks with Random APs
In conventional Wireless Mesh Networks (WMNs), multihop relays are performed in the backbone comprising of interconnected Mesh Routers (MRs) and this causes capacity degradation.
This paper proposes a hybrid WMN architecture that the backbone is able to utilize random connections to Access Points (APs) of Wireless Local Area Network (WLAN). In such a proposed hierarchal architecture, capacity enhancement can be achieved by letting the traffic take advantage of the wired connections through APs.
Theoretical analysis has been conducted for the asymptotic capacity of three-tier hybrid WMN, where per-MR capacity in the backbone is first derived and per-MC capacity is then obtained. Besides related to the number of MR cells as a conventional WMN, the analytical results reveal that the asymptotic capacity of a hybrid WMN is also strongly affected by the number of cells having AP connections, the ratio of access link bandwidth to backbone link bandwidth, etc.
Appropriate configuration of the network can drastically improve the network capacity in our proposed network architecture. It also shows that the traffic balance among the MRs with AP access is very important to have a tighter asymptotic capacity bound. The results and conclusions justify the perspective of having such a hybrid WMN utilizing widely deployed WLANs.
This paper proposes a hybrid WMN architecture that the backbone is able to utilize random connections to Access Points (APs) of Wireless Local Area Network (WLAN). In such a proposed hierarchal architecture, capacity enhancement can be achieved by letting the traffic take advantage of the wired connections through APs.
Theoretical analysis has been conducted for the asymptotic capacity of three-tier hybrid WMN, where per-MR capacity in the backbone is first derived and per-MC capacity is then obtained. Besides related to the number of MR cells as a conventional WMN, the analytical results reveal that the asymptotic capacity of a hybrid WMN is also strongly affected by the number of cells having AP connections, the ratio of access link bandwidth to backbone link bandwidth, etc.
Appropriate configuration of the network can drastically improve the network capacity in our proposed network architecture. It also shows that the traffic balance among the MRs with AP access is very important to have a tighter asymptotic capacity bound. The results and conclusions justify the perspective of having such a hybrid WMN utilizing widely deployed WLANs.
Channel Allocation and Routing in Hybrid Multichannel Multiradio Wireless Mesh Networks
Many efforts have been devoted to maximizing network throughput in a multichannel multiradio wireless mesh network. Most current solutions are based on either purely static or purely dynamic channel allocation approaches.
In this paper, we propose a hybrid multichannel multiradio wireless mesh networking architecture, where each mesh node has both static and dynamic interfaces. We first present an Adaptive Dynamic Channel Allocation protocol (ADCA), which considers optimization for both throughput and delay in the channel assignment.
In addition, we also propose an Interference and Congestion Aware Routing protocol (ICAR) in the hybrid network with both static and dynamic links, which balances the channel usage in the network.
Our simulation results show that compared to previous works, ADCA reduces the packet delay considerably without degrading the network throughput. The hybrid architecture shows much better adaptivity to changing traffic than purely static architecture without dramatic increase in overhead, and achieves lower delay than existing approaches for hybrid networks.
In this paper, we propose a hybrid multichannel multiradio wireless mesh networking architecture, where each mesh node has both static and dynamic interfaces. We first present an Adaptive Dynamic Channel Allocation protocol (ADCA), which considers optimization for both throughput and delay in the channel assignment.
In addition, we also propose an Interference and Congestion Aware Routing protocol (ICAR) in the hybrid network with both static and dynamic links, which balances the channel usage in the network.
Our simulation results show that compared to previous works, ADCA reduces the packet delay considerably without degrading the network throughput. The hybrid architecture shows much better adaptivity to changing traffic than purely static architecture without dramatic increase in overhead, and achieves lower delay than existing approaches for hybrid networks.
Coloring-Based Inter-WBAN Scheduling for Mobile Wireless Body Area Networks
In this study, random incomplete coloring (RIC) with low time-complexity and high spatial reuse is proposed to overcome in-between wireless-body-area-networks (WBAN) interference, which can cause serious throughput degradation and energy waste. Interference-avoidance scheduling of wireless networks can be modeled as a problem of graph coloring.
For instance, high spatial-reuse scheduling for a dense sensor network is mapped to high spatial-reuse coloring; fast convergence scheduling for a mobile ad hoc network (MANET) is mapped to low time-complexity coloring.
However, for a dense and mobile WBAN, inter-WBAN scheduling (IWS) should simultaneously satisfy both of the following requirements: 1) high spatial-reuse and 2) fast convergence, which are tradeoffs in conventional coloring. By relaxing the coloring rule, the proposed distributed coloring algorithm RIC avoids this tradeoff and satisfies both requirements.
Simulation results verify that the proposed coloring algorithm effectively overcomes inter-WBAN interference and invariably supports higher system throughput in various mobile WBAN scenarios compared to conventional colorings.
For instance, high spatial-reuse scheduling for a dense sensor network is mapped to high spatial-reuse coloring; fast convergence scheduling for a mobile ad hoc network (MANET) is mapped to low time-complexity coloring.
However, for a dense and mobile WBAN, inter-WBAN scheduling (IWS) should simultaneously satisfy both of the following requirements: 1) high spatial-reuse and 2) fast convergence, which are tradeoffs in conventional coloring. By relaxing the coloring rule, the proposed distributed coloring algorithm RIC avoids this tradeoff and satisfies both requirements.
Simulation results verify that the proposed coloring algorithm effectively overcomes inter-WBAN interference and invariably supports higher system throughput in various mobile WBAN scenarios compared to conventional colorings.
Cross-Layer Design of Congestion Control and Power Control in Fast-Fading Wireless Networks
Abstract
We study the cross-layer design of congestion control and power allocation with outage constraint in an interference-limited multihop wireless networks. Using a complete-convexification method, we first propose a message-passing distributed algorithm that can attain the global optimal source rate and link power allocation. Despite the attractiveness of its optimality, this algorithm requires larger message size than that of the conventional scheme, which increases network overheads.
Using the bounds on outage probability, we map the outage constraint to an SIR constraint and continue developing a practical near-optimal distributed algorithm requiring only local SIR measurement at link receivers to limit the size of the message. Due to the complicated complete-convexification method, however the congestion control of both algorithms no longer preserves the existing TCP stack.
To take into account the TCP stack preserving property, we propose the third algorithm using a successive convex approximation method to iteratively transform the original nonconvex problem into approximated convex problems, then the global optimal solution can converge distributively with message-passing. Thanks to the tightness of the bounds and successive approximations, numerical results show that the gap between three algorithms is almost indistinguishable.
Despite the same type of the complete-convexification method, the numerical comparison shows that the second near-optimal scheme has a faster convergence rate than that of the first optimal one, which make the near-optimal scheme more favorable and applicable in practice. Meanwhile, the third optimal scheme also has a faster convergence rate than that of a previous work using logarithm successive approximation method.
Using the bounds on outage probability, we map the outage constraint to an SIR constraint and continue developing a practical near-optimal distributed algorithm requiring only local SIR measurement at link receivers to limit the size of the message. Due to the complicated complete-convexification method, however the congestion control of both algorithms no longer preserves the existing TCP stack.
To take into account the TCP stack preserving property, we propose the third algorithm using a successive convex approximation method to iteratively transform the original nonconvex problem into approximated convex problems, then the global optimal solution can converge distributively with message-passing. Thanks to the tightness of the bounds and successive approximations, numerical results show that the gap between three algorithms is almost indistinguishable.
Despite the same type of the complete-convexification method, the numerical comparison shows that the second near-optimal scheme has a faster convergence rate than that of the first optimal one, which make the near-optimal scheme more favorable and applicable in practice. Meanwhile, the third optimal scheme also has a faster convergence rate than that of a previous work using logarithm successive approximation method.
DCIM: Distributed Cache Invalidation Method for Maintaining Cache Consistency in Wireless Mobile Networks
ABSTRACT:
This paper proposes distributed cache invalidation mechanism (DCIM), a client-based cache consistency scheme that is implemented on top of a previously proposed architecture for caching data items in mobile ad hoc networks (MANETs), namely COACS, where special nodes cache the queries and the addresses of the nodes that store the responses to these queries.
We have also previously proposed a server-based consistency scheme, named SSUM, whereas in this paper, we introduce DCIM that is totally client-based. DCIM is a pull-based algorithm that implements adaptive time to live (TTL), piggybacking, and prefetching, and provides near strong consistency capabilities.
Cached data items are assigned adaptive TTL values that correspond to their update rates at the data source, where items with expired TTL values are grouped in validation requests to the data source to refresh them, whereas unexpired ones but with high request rates are prefetched from the server.
In this paper, DCIM is analyzed to assess the delay and bandwidth gains (or costs) when compared to polling every time and push-based schemes. DCIM was also implemented using ns2, and compared against client-based and server-based schemes to assess its performance experimentally. The consistency ratio, delay, and overhead traffic are reported versus several variables, where DCIM showed to be superior when compared to the other systems.
We have also previously proposed a server-based consistency scheme, named SSUM, whereas in this paper, we introduce DCIM that is totally client-based. DCIM is a pull-based algorithm that implements adaptive time to live (TTL), piggybacking, and prefetching, and provides near strong consistency capabilities.
Cached data items are assigned adaptive TTL values that correspond to their update rates at the data source, where items with expired TTL values are grouped in validation requests to the data source to refresh them, whereas unexpired ones but with high request rates are prefetched from the server.
In this paper, DCIM is analyzed to assess the delay and bandwidth gains (or costs) when compared to polling every time and push-based schemes. DCIM was also implemented using ns2, and compared against client-based and server-based schemes to assess its performance experimentally. The consistency ratio, delay, and overhead traffic are reported versus several variables, where DCIM showed to be superior when compared to the other systems.
Delay Optimal Broadcast for Multihop Wireless Networks using Self –Interference Cancellation
Conventional wireless broadcast protocols rely heavily on the 802.11-based CSMA/CA model, which avoids interference and collision by conservative scheduling of transmissions. While CSMA/CA is amenable to multiple concurrent unicasts, it tends to degrade broadcast performance significantly, especially in lossy and large-scale networks.
In this paper, we propose a new protocol called Chorus that improves the efficiency and scalability of broadcast service with a MAC/PHY layer that allows packet collisions. Chorus is built upon the observation that packets carrying the same data can be effectively detected and decoded, even when they overlap with each other and have comparable signal strengths.
It resolves collision using symbol-level interference cancellation, and then combines the resolved symbols to restore the packet. Such a collision-tolerant mechanism significantly improves the transmission diversity and spatial reuse in wireless broadcast. Chorus' MAC-layer cognitive sensing and scheduling scheme further facilitates the realization of such an advantage, resulting in an asymptotic broadcast delay that is proportional to the network radius.
We evaluate Chorus' PHY-layer collision resolution mechanism with symbol-level simulation, and validate its network-level performance via ns-2, in comparison with a typical CSMA/CA-based broadcast protocol. Our evaluation validates Chorus's superior performance with respect to scalability, reliability, delay, etc., under a broad range of network scenarios (e.g., single/multiple broadcast sessions, static/mobile topologies).
In this paper, we propose a new protocol called Chorus that improves the efficiency and scalability of broadcast service with a MAC/PHY layer that allows packet collisions. Chorus is built upon the observation that packets carrying the same data can be effectively detected and decoded, even when they overlap with each other and have comparable signal strengths.
It resolves collision using symbol-level interference cancellation, and then combines the resolved symbols to restore the packet. Such a collision-tolerant mechanism significantly improves the transmission diversity and spatial reuse in wireless broadcast. Chorus' MAC-layer cognitive sensing and scheduling scheme further facilitates the realization of such an advantage, resulting in an asymptotic broadcast delay that is proportional to the network radius.
We evaluate Chorus' PHY-layer collision resolution mechanism with symbol-level simulation, and validate its network-level performance via ns-2, in comparison with a typical CSMA/CA-based broadcast protocol. Our evaluation validates Chorus's superior performance with respect to scalability, reliability, delay, etc., under a broad range of network scenarios (e.g., single/multiple broadcast sessions, static/mobile topologies).
Detection and Localization of Multiple Spoofing Attackers in Wireless Networks
Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements.
In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks.
We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers.
In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings.
Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.
In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks.
We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers.
In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings.
Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.
Discovery and Verification of Neighbor Positions in Mobile Ad Hoc Networks
A growing number of ad hoc networking protocols and location-aware services require that mobile nodes learn the position of their neighbors. However, such a process can be easily abused or disrupted by adversarial nodes.
In absence of a priori trusted nodes, the discovery and verification of neighbor positions presents challenges that have been scarcely investigated in the literature. In this paper, we address this open issue by proposing a fully distributed cooperative solution that is robust against independent and colluding adversaries, and can be impaired only by an overwhelming presence of adversaries.
Results show that our protocol can thwart more than 99 percent of the attacks under the best possible conditions for the adversaries, with minimal false positive rates.
In absence of a priori trusted nodes, the discovery and verification of neighbor positions presents challenges that have been scarcely investigated in the literature. In this paper, we address this open issue by proposing a fully distributed cooperative solution that is robust against independent and colluding adversaries, and can be impaired only by an overwhelming presence of adversaries.
Results show that our protocol can thwart more than 99 percent of the attacks under the best possible conditions for the adversaries, with minimal false positive rates.
Distance Bounding: A Practical Security Solution for Real-Time Location Systems
The need for implementing adequate security services in industrial applications is increasing. Verifying the physical proximity or location of a device has become an important security service in ad-hoc wireless environments.
Distance-bounding is a prominent secure neighbor detection method that cryptographically determines an upper bound for the physical distance between two communicating parties based on the round-trip time of cryptographic challenge-response pairs.
This paper gives a brief overview of distance-bounding protocols and discusses the possibility of implementing such protocols within industrial RFID and real-time location applications, which requires an emphasis on aspects such as reliability and real-time communication.
The practical resource requirements and performance tradeoffs involved are illustrated using a sample of distance-bounding proposals, and some remaining research challenges with regards to practical implementation are discussed.
Distance-bounding is a prominent secure neighbor detection method that cryptographically determines an upper bound for the physical distance between two communicating parties based on the round-trip time of cryptographic challenge-response pairs.
This paper gives a brief overview of distance-bounding protocols and discusses the possibility of implementing such protocols within industrial RFID and real-time location applications, which requires an emphasis on aspects such as reliability and real-time communication.
The practical resource requirements and performance tradeoffs involved are illustrated using a sample of distance-bounding proposals, and some remaining research challenges with regards to practical implementation are discussed.
Distributed Cooperative Caching in Social Wireless Networks
This paper introduces cooperative caching policies for minimizing electronic content provisioning cost in Social Wireless Networks (SWNET). SWNETs are formed by mobile devices, such as data enabled phones, electronic book readers etc., sharing common interests in electronic content, and physically gathering together in public places.
Electronic object caching in such SWNETs are shown to be able to reduce the content provisioning cost which depends heavily on the service and pricing dependences among various stakeholders including content providers (CP), network service providers, and End Consumers (EC).
Drawing motivation from Amazon's Kindle electronic book delivery business, this paper develops practical network, service, and pricing models which are then used for creating two object caching strategies for minimizing content provisioning costs in networks with homogenous and heterogeneous object demands.
The paper constructs analytical and simulation models for analyzing the proposed caching strategies in the presence of selfish users that deviate from network-wide cost-optimal policies. It also reports results from an Android phone-based prototype SWNET, validating the presented analytical and simulation results.
Electronic object caching in such SWNETs are shown to be able to reduce the content provisioning cost which depends heavily on the service and pricing dependences among various stakeholders including content providers (CP), network service providers, and End Consumers (EC).
Drawing motivation from Amazon's Kindle electronic book delivery business, this paper develops practical network, service, and pricing models which are then used for creating two object caching strategies for minimizing content provisioning costs in networks with homogenous and heterogeneous object demands.
The paper constructs analytical and simulation models for analyzing the proposed caching strategies in the presence of selfish users that deviate from network-wide cost-optimal policies. It also reports results from an Android phone-based prototype SWNET, validating the presented analytical and simulation results.
EAACK—A Secure Intrusion-Detection System for MANETs
The migration to wireless network from wired network has been a global trend in the past few decades. The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless networks, Mobile Ad hoc NETwork (MANET) is one of the most important and unique applications. On the contrary to traditional network architecture, MANET does not require a fixed network infrastructure; every single node works as both a transmitter and a receiver.
Nodes communicate directly with each other when they are both within the same communication range. Otherwise, they rely on their neighbors to relay messages. The self-configuring ability of nodes in MANET made it popular among critical mission applications like military use or emergency recovery.
However, the open medium and wide distribution of nodes make MANET vulnerable to malicious attackers. In this case, it is crucial to develop efficient intrusion-detection mechanisms to protect MANET from attacks. With the improvements of the technology and cut in hardware costs, we are witnessing a current trend of expanding MANETs into industrial applications.
To adjust to such trend, we strongly believe that it is vital to address its potential security issues. In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowledgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher malicious-behavior-detection rates in certain circumstances while does not greatly affect the network performances.
Nodes communicate directly with each other when they are both within the same communication range. Otherwise, they rely on their neighbors to relay messages. The self-configuring ability of nodes in MANET made it popular among critical mission applications like military use or emergency recovery.
However, the open medium and wide distribution of nodes make MANET vulnerable to malicious attackers. In this case, it is crucial to develop efficient intrusion-detection mechanisms to protect MANET from attacks. With the improvements of the technology and cut in hardware costs, we are witnessing a current trend of expanding MANETs into industrial applications.
To adjust to such trend, we strongly believe that it is vital to address its potential security issues. In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowledgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher malicious-behavior-detection rates in certain circumstances while does not greatly affect the network performances.
Efficient Algorithms for Neighbor Discovery in Wireless Networks
Neighbor discovery is an important first step in the initialization of a wireless ad hoc network. In this paper, we design and analyze several algorithms for neighbor discovery in wireless networks. Starting with a single-hop wireless network of n nodes, we propose a Θ(nlnn) ALOHA-like neighbor discovery algorithm when nodes cannot detect collisions, and an order-optimal Θ(n) receiver feedback-based algorithm when nodes can detect collisions. Our algorithms neither require nodes to have a priori estimates of the number of neighbors nor synchronization between nodes.
Our algorithms allow nodes to begin execution at different time instants and to terminate neighbor discovery upon discovering all their neighbors. We finally show that receiver feedback can be used to achieve a Θ(n) running time, even when nodes cannot detect collisions.
We then analyze neighbor discovery in a general multihop setting. We establish an upper bound of O(Δlnn) on the running time of the ALOHA-like algorithm, where Δ denotes the maximum node degree in the network and n the total number of nodes.
We also establish a lower bound of Ω(Δ+lnn) on the running time of any randomized neighbor discovery algorithm. Our result thus implies that the ALOHA-like algorithm is at most a factor min(Δ,lnn) worse than optimal.
Our algorithms allow nodes to begin execution at different time instants and to terminate neighbor discovery upon discovering all their neighbors. We finally show that receiver feedback can be used to achieve a Θ(n) running time, even when nodes cannot detect collisions.
We then analyze neighbor discovery in a general multihop setting. We establish an upper bound of O(Δlnn) on the running time of the ALOHA-like algorithm, where Δ denotes the maximum node degree in the network and n the total number of nodes.
We also establish a lower bound of Ω(Δ+lnn) on the running time of any randomized neighbor discovery algorithm. Our result thus implies that the ALOHA-like algorithm is at most a factor min(Δ,lnn) worse than optimal.
Enhanced OLSR for defense against DOS attack in ad hoc networks
Mobile ad hoc networks (MANET) refers to a network designed for special applications for which it is difficult to use a backbone network. In MANETs, applications are mostly involved with sensitive and secret information. Since MANET assumes a trusted environment for routing, security is a major issue.
In this paper we analyze the vulnerabilities of a pro-active routing protocol called optimized link state routing (OLSR) against a specific type of denial-of-service (DOS) attack called node isolation attack. Analyzing the attack, we propose a mechanism called enhanced OLSR (EOLSR) protocol which is a trust based technique to secure the OLSR nodes against the attack.
Our technique is capable of finding whether a node is advertising correct topology information or not by verifying its Hello packets, thus detecting node isolation attacks.
The experiment results show that our protocol is able to achieve routing security with 45% increase in packet delivery ratio and 44% reduction in packet loss rate when compared to standard OLSR under node isolation attack. Our technique is light weight because it doesn't involve high computational complexity for securing the network.
In this paper we analyze the vulnerabilities of a pro-active routing protocol called optimized link state routing (OLSR) against a specific type of denial-of-service (DOS) attack called node isolation attack. Analyzing the attack, we propose a mechanism called enhanced OLSR (EOLSR) protocol which is a trust based technique to secure the OLSR nodes against the attack.
Our technique is capable of finding whether a node is advertising correct topology information or not by verifying its Hello packets, thus detecting node isolation attacks.
The experiment results show that our protocol is able to achieve routing security with 45% increase in packet delivery ratio and 44% reduction in packet loss rate when compared to standard OLSR under node isolation attack. Our technique is light weight because it doesn't involve high computational complexity for securing the network.
Exploiting Ubiquitous Data Collection for Mobile Users in Wireless Sensor Networks
We study the ubiquitous data collection for mobile users in wireless sensor networks. People with handheld devices can easily interact with the network and collect data. We propose a novel approach for mobile users to collect the network-wide data.
The routing structure of data collection is additively updated with the movement of the mobile user. With this approach, we only perform a limited modification to update the routing structure while the routing performance is bounded and controlled compared to the optimal performance.
The proposed protocol is easy to implement. Our analysis shows that the proposed approach is scalable in maintenance overheads, performs efficiently in the routing performance, and provides continuous data delivery during the user movement.
We implement the proposed protocol in a prototype system and test its feasibility and applicability by a 49-node testbed. We further conduct extensive simulations to examine the efficiency and scalability of our protocol with varied network settings.
The routing structure of data collection is additively updated with the movement of the mobile user. With this approach, we only perform a limited modification to update the routing structure while the routing performance is bounded and controlled compared to the optimal performance.
The proposed protocol is easy to implement. Our analysis shows that the proposed approach is scalable in maintenance overheads, performs efficiently in the routing performance, and provides continuous data delivery during the user movement.
We implement the proposed protocol in a prototype system and test its feasibility and applicability by a 49-node testbed. We further conduct extensive simulations to examine the efficiency and scalability of our protocol with varied network settings.
Harvesting-Aware Energy Management for Time-Critical Wireless Sensor Networks With Joint Voltage and Modulation Scaling
As Cyber-Physical-Systems (CPSs) evolve they will be increasingly relied on to support time-critical and performance-intensive monitoring and control activities. Further, many CPSs that utilize Wireless Sensor Networking (WSN) technologies will require the use of energy harvesting methods to extend their lifetimes.
For this application class, there are currently few algorithmic techniques that combine performance sensitive processing and communication with efficient management techniques for energy harvesting. Our paper addresses this problem. We first propose a general purpose, multihop WSN architecture capable of supporting time-critical CPS systems using energy harvesting. We then present a set of Harvesting Aware Speed Selection (HASS) algorithms.
Our technique maximizes the minimum energy reserve for all the nodes in the network, thus ensuring highly resilient performance under emergency or fault-driven situations. We present an optimal centralized solution, along with an efficient, distributed solution.
We propose a CPS-specific experimental methodology, enabling us to evaluate our approach. Our experiments show that our algorithms yield significantly higher energy reserves than baseline methods.
For this application class, there are currently few algorithmic techniques that combine performance sensitive processing and communication with efficient management techniques for energy harvesting. Our paper addresses this problem. We first propose a general purpose, multihop WSN architecture capable of supporting time-critical CPS systems using energy harvesting. We then present a set of Harvesting Aware Speed Selection (HASS) algorithms.
Our technique maximizes the minimum energy reserve for all the nodes in the network, thus ensuring highly resilient performance under emergency or fault-driven situations. We present an optimal centralized solution, along with an efficient, distributed solution.
We propose a CPS-specific experimental methodology, enabling us to evaluate our approach. Our experiments show that our algorithms yield significantly higher energy reserves than baseline methods.
In-Network Estimation with Delay Constraints in Wireless Sensor Networks
The use of wireless sensor networks (WSNs) for closing the loops between the cyberspace and the physical processes is more attractive and promising for future control systems. For some real-time control applications, controllers need to accurately estimate the process state within rigid delay constraints. In this paper, we propose a novel in-network estimation approach for state estimation with delay constraints in multihop WSNs.
For accurately estimating a process state as well as satisfying rigid delay constraints, we address the problem through jointly designing in-network estimation operations and an aggregation scheduling algorithm.
Our in-network estimation operation performed at relays not only optimally fuses the estimates obtained from the different sensors but also predicts the upper stream sensors' estimates which cannot be aggregated to the sink before deadlines.
Our estimate aggregation scheduling algorithm, which is interference free, is able to aggregate as much estimate information as possible from the network to the sink within delay constraints. We proved the unbiasedness of in-network estimation, and theoretically analyzed the optimality of our approach.
Our simulation results corroborate our theoretical results and show that our in-network estimation approach can obtain significant estimation accuracy gain under different network settings.
For accurately estimating a process state as well as satisfying rigid delay constraints, we address the problem through jointly designing in-network estimation operations and an aggregation scheduling algorithm.
Our in-network estimation operation performed at relays not only optimally fuses the estimates obtained from the different sensors but also predicts the upper stream sensors' estimates which cannot be aggregated to the sink before deadlines.
Our estimate aggregation scheduling algorithm, which is interference free, is able to aggregate as much estimate information as possible from the network to the sink within delay constraints. We proved the unbiasedness of in-network estimation, and theoretically analyzed the optimality of our approach.
Our simulation results corroborate our theoretical results and show that our in-network estimation approach can obtain significant estimation accuracy gain under different network settings.
Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are increasingly used in data-intensive applications such as microclimate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit all the data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies.
We propose using low-cost disposable mobile relays to reduce the energy consumption of data-intensive WSNs. Our approach differs from previous work in two main aspects.
First, it does not require complex motion planning of mobile nodes, so it can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless transmissions into a holistic optimization framework. Our framework consists of three main algorithms. The first algorithm computes an optimal routing tree assuming no nodes can move.
The second algorithm improves the topology of the routing tree by greedily adding new nodes exploiting mobility of the newly added nodes. The third algorithm improves the routing tree by relocating its nodes without changing its topology. This iterative algorithm converges on the optimal position for each node given the constraint that the routing tree topology does not change.
We present efficient distributed implementations for each algorithm that require only limited, localized synchronization. Because we do not necessarily compute an optimal topology, our final routing tree is not necessarily optimal. However, our simulation results show that our algorithms significantly outperform the best existing solutions
We propose using low-cost disposable mobile relays to reduce the energy consumption of data-intensive WSNs. Our approach differs from previous work in two main aspects.
First, it does not require complex motion planning of mobile nodes, so it can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless transmissions into a holistic optimization framework. Our framework consists of three main algorithms. The first algorithm computes an optimal routing tree assuming no nodes can move.
The second algorithm improves the topology of the routing tree by greedily adding new nodes exploiting mobility of the newly added nodes. The third algorithm improves the routing tree by relocating its nodes without changing its topology. This iterative algorithm converges on the optimal position for each node given the constraint that the routing tree topology does not change.
We present efficient distributed implementations for each algorithm that require only limited, localized synchronization. Because we do not necessarily compute an optimal topology, our final routing tree is not necessarily optimal. However, our simulation results show that our algorithms significantly outperform the best existing solutions
Model-Based Analysis of Wireless System Architectures for Real-Time Applications
We propose a model-based description and analysis framework for the design of wireless system architectures. Its aim is to address the shortcomings of existing approaches to system verification and the tracking of anomalies in safety-critical wireless systems. We use Architecture Analysis and Description Language (AADL) to describe an analysis-oriented architecture model with highly modular components.
We also develop the cooperative tool chains required to analyze the performance of a wireless system by simulation. We show how this framework can support a detailed and largely automated analysis of a complicated, networked wireless system using examples from wireless healthcare and video broadcasting.
We also develop the cooperative tool chains required to analyze the performance of a wireless system by simulation. We show how this framework can support a detailed and largely automated analysis of a complicated, networked wireless system using examples from wireless healthcare and video broadcasting.
Network Traffic Classification Using Correlation Information
Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent research tends to apply machine learning techniques to flow statistical feature based classification methods. The nearest neighbor (NN)-based method has exhibited superior classification performance.
It also has several important advantages, such as no requirements of training procedure, no risk of overfitting of parameters, and naturally being able to handle a huge number of classes. However, the performance of NN classifier can be severely affected if the size of training data is small.
In this paper, we propose a novel nonparametric approach for traffic classification, which can improve the classification performance effectively by incorporating correlated information into the classification process. We analyze the new classification approach and its performance benefit from both theoretical and empirical perspectives.
A large number of experiments are carried out on two real-world traffic data sets to validate the proposed approach. The results show the traffic classification performance can be improved significantly even under the extreme difficult circumstance of very few training samples.
It also has several important advantages, such as no requirements of training procedure, no risk of overfitting of parameters, and naturally being able to handle a huge number of classes. However, the performance of NN classifier can be severely affected if the size of training data is small.
In this paper, we propose a novel nonparametric approach for traffic classification, which can improve the classification performance effectively by incorporating correlated information into the classification process. We analyze the new classification approach and its performance benefit from both theoretical and empirical perspectives.
A large number of experiments are carried out on two real-world traffic data sets to validate the proposed approach. The results show the traffic classification performance can be improved significantly even under the extreme difficult circumstance of very few training samples.
On Exploiting Transient Social Contact Patterns for Data Forwarding in Delay-Tolerant Networks
Unpredictable node mobility, low node density, and lack of global information make it challenging to achieve effective data forwarding in Delay-Tolerant Networks (DTNs). Most of the current data forwarding schemes choose the nodes with the best cumulative capability of contacting others as relays to carry and forward data, but these nodes may not be the best relay choices within a short time period due to the heterogeneity of transient node contact characteristics.
In this paper, we propose a novel approach to improve the performance of data forwarding with a short time constraint in DTNs by exploiting the transient social contact patterns. These patterns represent the transient characteristics of contact distribution, network connectivity and social community structure in DTNs, and we provide analytical formulations on these patterns based on experimental studies of realistic DTN traces.
We then propose appropriate forwarding metrics based on these patterns to improve the effectiveness of data forwarding. When applied to various data forwarding strategies, our proposed forwarding metrics achieve much better performance compared to existing schemes with similar forwarding cost.
In this paper, we propose a novel approach to improve the performance of data forwarding with a short time constraint in DTNs by exploiting the transient social contact patterns. These patterns represent the transient characteristics of contact distribution, network connectivity and social community structure in DTNs, and we provide analytical formulations on these patterns based on experimental studies of realistic DTN traces.
We then propose appropriate forwarding metrics based on these patterns to improve the effectiveness of data forwarding. When applied to various data forwarding strategies, our proposed forwarding metrics achieve much better performance compared to existing schemes with similar forwarding cost.
Opportunistic MANETs: Mobility Can Make Up for Low Transmission Power
ABSTRACT:
Opportunistic mobile ad hoc networks (MANETs) are a special class of sparse and disconnected MANETs where data communication exploits sporadic contact opportunities among nodes. We consider opportunistic MANETs where nodes move independently at random over a square of the plane.
Nodes exchange data if they are at a distance at most within each other, where is the node transmission radius. The flooding time is the number of time-steps required to broadcast a message from a source node to every node of the network.
Flooding time is an important measure of how fast information can spread in dynamic networks. We derive the first upper bound on the flooding time, which is a decreasing function of the maximal speed of the nodes.
The bound holds with high probability, and it is nearly tight. Our bound shows that, thanks to node mobility, even when the network is sparse and disconnected, information spreading can be fast.
Nodes exchange data if they are at a distance at most within each other, where is the node transmission radius. The flooding time is the number of time-steps required to broadcast a message from a source node to every node of the network.
Flooding time is an important measure of how fast information can spread in dynamic networks. We derive the first upper bound on the flooding time, which is a decreasing function of the maximal speed of the nodes.
The bound holds with high probability, and it is nearly tight. Our bound shows that, thanks to node mobility, even when the network is sparse and disconnected, information spreading can be fast.
Optimal multicast capacity and delay tradeoffs in MANETs: A global perspective
In this paper, we give a global perspective of multicast capacity and delay analysis in Mobile Ad-hoc Networks (MANETs).
Specifically, we consider two node mobility models: (1) two-dimensional i.i.d. mobility, (2) one-dimensional i.i.d. mobility. Two mobility time-scales are included in this paper: (i) Fast mobility where node mobility is at the same time-scale as data transmissions; (ii) Slow mobility where node mobility is assumed to occur at a much slower time-scale than data transmissions.
Given a delay constraint D, we first characterize the optimal multicast capacity for each of the four mobility models, and then we develop a scheme that can achieve a capacity-delay tradeoff close to the upper bound up to a logarithmic factor.
Our study can be further extended to two-dimensional/one-dimensional hybrid random walk fast/slow mobility models and heterogeneous networks.
Specifically, we consider two node mobility models: (1) two-dimensional i.i.d. mobility, (2) one-dimensional i.i.d. mobility. Two mobility time-scales are included in this paper: (i) Fast mobility where node mobility is at the same time-scale as data transmissions; (ii) Slow mobility where node mobility is assumed to occur at a much slower time-scale than data transmissions.
Given a delay constraint D, we first characterize the optimal multicast capacity for each of the four mobility models, and then we develop a scheme that can achieve a capacity-delay tradeoff close to the upper bound up to a logarithmic factor.
Our study can be further extended to two-dimensional/one-dimensional hybrid random walk fast/slow mobility models and heterogeneous networks.
Power Allocation for Statistical QoS Provisioning in Opportunistic Multi-Relay DF Cognitive Networks
In this letter, we propose a power allocation scheme for statistical quality-of-service (QoS) provisioning in multi-relay decode-and-forward (DF) cognitive networks (CN). By considering the direct link between the source and destination, the CN first chooses the transmission mode (direct transmission or relay transmission) based on the channel state information.
Then, according to the determined transmission mode, efficient power allocation will be performed under the given QoS requirement, the average transmit and interference power constraints as well as the peak interference constraint.
Our proposed power allocation scheme indicates that, in order to achieve the maximum throughput, at most two relays can be involved for the transmission. Simulation results show that our proposed scheme outperforms the max-min criterion and equal power allocation policy.
Then, according to the determined transmission mode, efficient power allocation will be performed under the given QoS requirement, the average transmit and interference power constraints as well as the peak interference constraint.
Our proposed power allocation scheme indicates that, in order to achieve the maximum throughput, at most two relays can be involved for the transmission. Simulation results show that our proposed scheme outperforms the max-min criterion and equal power allocation policy.
Proteus: Multiflow Diversity Routing for Wireless Networks with Cooperative Transmissions
ABSTRACT:
In this paper, we consider the use of cooperative transmissions in multihop wireless networks to achieve Virtual Multiple Input Single Output (VMISO) links. Specifically, we investigate how the physical layer VMISO benefits translate into network level performance improvements.
We show that the improvements are nontrivial (15 to 300 percent depending on the node density) but rely on two crucial algorithmic decisions: the number of cooperating transmitters for each link; and the cooperation strategy used by the transmitters. We explore the tradeoffs in making routing decisions using analytical models and derive the key routing considerations.
Finally, we present Proteus, an adaptive diversity routing protocol that includes algorithmic solutions to the above two decision problems and leverages VMISO links in multihop wireless network to achieve performance improvements.
We evaluate Proteus using NS2-based simulations with an enhanced physical layer model that accurately captures the effect of VMISO transmissions
We show that the improvements are nontrivial (15 to 300 percent depending on the node density) but rely on two crucial algorithmic decisions: the number of cooperating transmitters for each link; and the cooperation strategy used by the transmitters. We explore the tradeoffs in making routing decisions using analytical models and derive the key routing considerations.
Finally, we present Proteus, an adaptive diversity routing protocol that includes algorithmic solutions to the above two decision problems and leverages VMISO links in multihop wireless network to achieve performance improvements.
We evaluate Proteus using NS2-based simulations with an enhanced physical layer model that accurately captures the effect of VMISO transmissions
Quality-Differentiated Video Multicast in Multirate Wireless Networks
Adaptation of modulation and transmission bit-rates for video multicast in a multirate wireless network is a challenging problem because of network dynamics, variable video bit-rates, and heterogeneous clients who may expect differentiated video qualities.
Prior work on the leader-based schemes selects the transmission bit-rate that provides reliable transmission for the node that experiences the worst channel condition. However, this may penalize other nodes that can achieve a higher throughput by receiving at a higher rate.
In this work, we investigate a rate-adaptive video multicast scheme that can provide heterogeneous clients differentiated visual qualities matching their channel conditions. We first propose a rate scheduling model that selects the optimal transmission bit-rate for each video frame to maximize the total visual quality for a multicast group subject to the minimum-visual-quality-guaranteed constraint.
We then present a practical and easy-to-implement protocol, called QDM, which constructs a cluster-based structure to characterize node heterogeneity and adapts the transmission bit-rate to network dynamics based on video quality perceived by the representative cluster heads.
Since QDM selects the rate by a sample-based technique, it is suitable for real-time streaming even without any preprocess. We show that QDM can adapt to network dynamics and variable video-bit rates efficiently, and produce a gain of 2-5 dB in terms of the average video quality as compared to the leader-based approach.
Prior work on the leader-based schemes selects the transmission bit-rate that provides reliable transmission for the node that experiences the worst channel condition. However, this may penalize other nodes that can achieve a higher throughput by receiving at a higher rate.
In this work, we investigate a rate-adaptive video multicast scheme that can provide heterogeneous clients differentiated visual qualities matching their channel conditions. We first propose a rate scheduling model that selects the optimal transmission bit-rate for each video frame to maximize the total visual quality for a multicast group subject to the minimum-visual-quality-guaranteed constraint.
We then present a practical and easy-to-implement protocol, called QDM, which constructs a cluster-based structure to characterize node heterogeneity and adapts the transmission bit-rate to network dynamics based on video quality perceived by the representative cluster heads.
Since QDM selects the rate by a sample-based technique, it is suitable for real-time streaming even without any preprocess. We show that QDM can adapt to network dynamics and variable video-bit rates efficiently, and produce a gain of 2-5 dB in terms of the average video quality as compared to the leader-based approach.
Strategies for Energy-Efficient Resource Management of Hybrid Programming Models
Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes.
Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation.
The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems.
In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations.
We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss
Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation.
The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems.
In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations.
We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss
Target Tracking and Mobile Sensor Navigation in Wireless Sensor Networks
This work studies the problem of tracking signal-emitting mobile targets using navigated mobile sensors based on signal reception. Since the mobile target's maneuver is unknown, the mobile sensor controller utilizes the measurement collected by a wireless sensor network in terms of the mobile target signal's time of arrival (TOA).
The mobile sensor controller acquires the TOA measurement information from both the mobile target and the mobile sensor for estimating their locations before directing the mobile sensor's movement to follow the target. We propose a min-max approximation approach to estimate the location for tracking which can be efficiently solved via semidefinite programming (SDP) relaxation, and apply a cubic function for mobile sensor navigation.
We estimate the location of the mobile sensor and target jointly to improve the tracking accuracy. To further improve the system performance, we propose a weighted tracking algorithm by using the measurement information more efficiently. Our results demonstrate that the proposed algorithm provides good tracking performance and can quickly direct the mobile sensor to follow the mobile target.
The mobile sensor controller acquires the TOA measurement information from both the mobile target and the mobile sensor for estimating their locations before directing the mobile sensor's movement to follow the target. We propose a min-max approximation approach to estimate the location for tracking which can be efficiently solved via semidefinite programming (SDP) relaxation, and apply a cubic function for mobile sensor navigation.
We estimate the location of the mobile sensor and target jointly to improve the tracking accuracy. To further improve the system performance, we propose a weighted tracking algorithm by using the measurement information more efficiently. Our results demonstrate that the proposed algorithm provides good tracking performance and can quickly direct the mobile sensor to follow the mobile target.
Toward a Statistical Framework for Source Anonymity in Sensor Networks
In certain applications, the locations of events reported by a sensor network need to remain anonymous. That is, unauthorized observers must be unable to detect the origin of such events by analyzing the network traffic. Known as the source anonymity problem, this problem has emerged as an important topic in the security of wireless sensor networks, with variety of techniques based on different adversarial assumptions being proposed.
In this work, we present a new framework for modeling, analyzing, and evaluating anonymity in sensor networks. The novelty of the proposed framework is twofold: first, it introduces the notion of "interval indistinguishability” and provides a quantitative measure to model anonymity in wireless sensor networks; second, it maps source anonymity to the statistical problem of binary hypothesis testing with nuisance parameters. We then analyze existing solutions for designing anonymous sensor networks using the proposed model.
We show how mapping source anonymity to binary hypothesis testing with nuisance parameters leads to converting the problem of exposing private source information into searching for an appropriate data transformation that removes or minimize the effect of the nuisance information.
By doing so, we transform the problem from analyzing real-valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous sensor networks. Finally, we discuss how existing solutions can be modified to improve their anonymity.
In this work, we present a new framework for modeling, analyzing, and evaluating anonymity in sensor networks. The novelty of the proposed framework is twofold: first, it introduces the notion of "interval indistinguishability” and provides a quantitative measure to model anonymity in wireless sensor networks; second, it maps source anonymity to the statistical problem of binary hypothesis testing with nuisance parameters. We then analyze existing solutions for designing anonymous sensor networks using the proposed model.
We show how mapping source anonymity to binary hypothesis testing with nuisance parameters leads to converting the problem of exposing private source information into searching for an appropriate data transformation that removes or minimize the effect of the nuisance information.
By doing so, we transform the problem from analyzing real-valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous sensor networks. Finally, we discuss how existing solutions can be modified to improve their anonymity.
Toward Privacy Preserving and Collusion Resistance in a Location Proof Updating System
Today's location-sensitive service relies on user's mobile device to determine the current location. This allows malicious users to access a restricted resource or provide bogus alibis by cheating on their locations.
To address this issue, we propose A Privacy-Preserving LocAtion proof Updating System (APPLAUS) in which colocated Bluetooth enabled mobile devices mutually generate location proofs and send updates to a location proof server. Periodically changed pseudonyms are used by the mobile devices to protect source location privacy from each other, and from the untrusted location proof server.
We also develop user-centric location privacy model in which individual users evaluate their location privacy levels and decide whether and when to accept the location proof requests. In order to defend against colluding attacks, we also present betweenness ranking-based and correlation clustering-based approaches for outlier detection.
APPLAUS can be implemented with existing network infrastructure, and can be easily deployed in Bluetooth enabled mobile devices with little computation or power cost. Extensive experimental results show that APPLAUS can effectively provide location proofs, significantly preserve the source location privacy, and effectively detect colluding attacks.
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To address this issue, we propose A Privacy-Preserving LocAtion proof Updating System (APPLAUS) in which colocated Bluetooth enabled mobile devices mutually generate location proofs and send updates to a location proof server. Periodically changed pseudonyms are used by the mobile devices to protect source location privacy from each other, and from the untrusted location proof server.
We also develop user-centric location privacy model in which individual users evaluate their location privacy levels and decide whether and when to accept the location proof requests. In order to defend against colluding attacks, we also present betweenness ranking-based and correlation clustering-based approaches for outlier detection.
APPLAUS can be implemented with existing network infrastructure, and can be easily deployed in Bluetooth enabled mobile devices with little computation or power cost. Extensive experimental results show that APPLAUS can effectively provide location proofs, significantly preserve the source location privacy, and effectively detect colluding attacks.
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