In autonomous mobile ad hoc networks (MANETs) where each user is its own authority, the issue of cooperation enforcement must be solved first to enable networking functionalities such as packet forwarding, which becomes very difficult under noisy and imperfect monitoring. In this paper, we consider cooperation enforcement in autonomous mobile ad hoc networks under noisy and imperfect observation and study the basic packet forwarding among users through the repeated game models with imperfect information. A belief evaluation framework is proposed to obtain cooperation-enforcement packet forwarding strategies only based on each node's private information including its own past actions and imperfect observation of other nodes' information. More importantly, we not only show that the proposed strategy with belief system can maintain the cooperation paradigm but also establish its performance bounds. The simulation results illustrate that the proposed belief evaluation framework can enforce the cooperation with only a small performance degradation compared with the unconditionally cooperative outcomes when noisy and imperfect observation exist.

Cooperative communications represent a potential candidate to combat the effects of channel fading and to increase the transmit energy efficiency in wireless sensor networks with the downside being the increased complexity. In sensor networks the power consumed in the receiving and processing circuitry can constitute a significant portion of the total consumed power. By taking into consideration such overhead, an analytical framework for studying the energy efficiency trade-off of cooperation in sensor networks is presented. This trade-off is shown to depend on several parameters such as the receive and processing power, the required quality-of-service, the power amplifier loss, and several other factors. The analytical and numerical results reveal that for small distance separation between the source and destination, direct transmission is more energy efficient than relaying. The results also reveal that equal power allocation performs as well as optimal power allocation for some scenarios. The effects of the relay location and the number of employed relays on energy efficiency are also investigated in this work. Moreover, there are experimental results conducted to verify the channel model assumed in the article.

In self-organized mobile ad hoc networks (MANETs) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other or honestly revealing its private information, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by awarding some payment for cooperative behaviors. In this paper, we consider efficient routing in self-organized MANETs and model it as multi-stage dynamic pricing games. A game theoretical framework for dynamic pricing-based routing in MANETs is proposed to maximize the sender/receiveriquests payoff by considering the dynamic nature of MANETs. Meanwhile, the forwarding incentives of the relay nodes can also be maintained by optimally pricing their packet-forwarding services based on the auction rules and introducing the cartel maintenance enforcing mechanism. The simulation results illustrate that the proposed dynamic pricing-based routing approach has significant performance gains over the existing static pricing approaches.

In autonomous mobile ad-hoc networks, one major challenge is to stimulate cooperation among selfish nodes, especially when some nodes may be malicious. In this paper, we address cooperation stimulation in realistic yet challenging contexts where the environment is noisy and the underlying monitoring is imperfect. We have first explored the underlying reasons why stimulating cooperation under such scenarios is difficult. Instead of trying to enforce all nodes to act fully cooperatively, our goal is to stimulate cooperation in a hostile environment as much as possible through playing conditional altruism. To formally address the problem, we have modeled the interactions among nodes as secure routing and packet forwarding games under noise and imperfect observation, and devised a set of reputation-based attack-resistant cooperation strategies without requiring any tamper-proof hardware or central banking service. The performance of the devised strategies has also been evaluated analytically. The limitations of the game-theoretic approaches and the practicability of the devised strategies have also been investigated through theoretical analysis and extensive simulation studies. The results have demonstrated that although sometimes a gap may exist between the ideal game model and the reality, game-theoretic analysis can still provide thoughtful insights and useful guidelines when designing cooperation strategies.

Although a contributory group key agreement is a promising solution to achieve access control in collaborative and dynamic group applications, the existing schemes have not achieved the performance lower bound in terms of time, communication, and computation costs. In this paper, we propose a contributory group key agreement that achieves the performance lower bound by utilizing a novel logical key tree structure, called PFMH, and the concept of phantom user position. In particular, the proposed scheme only needsO(1) rounds of the two-party Diffie-Hellman (DH) upon any single-user join event andO(logn) rounds of the two-party DH upon any single-user leave event. Both the theoretical bound analysis and simulation show that the proposed scheme achieves a lower rekeying cost than the existing tree-based contributory group key agreement schemes.

In cooperative ad-hoc networks, nodes belong to the same authority and pursue the common goals, and will usually unconditionally help each other. Consequently, without necessary countermeasures, such networks are extremely vulnerable to insider attacks, especially under noise and imperfect monitoring. In this paper, we present a game theoretic analysis of securing cooperative ad-hoc networks against insider attacks in the presence of noise and imperfect monitoring. By focusing on the most basic networking function, namely routing and packet forwarding, we model the interactions between good nodes and insider attackers as secure routing and packet forwarding games. The worst case scenarios are studied where initially good nodes do not know who the attackers are while insider attackers know who are good. The optimal defense strategies have been devised in the sense that no other strategies can further increase the good nodes' payoff under attacks. Meanwhile, the optimal attacking strategies and the maximum possible damage that can be caused by attackers have been discussed. Extensive simulation studies have also been conducted to evaluate the effectiveness of the proposed strategies

In ad-hoc networks, nodes need to cooperatively forward packets for each other. Without necessary countermeasures, such networks are extremely vulnerable to injecting traffic attacks, especially those launched by insider attackers. Injecting an overwhelming amount of traffic into the network can easily cause network congestion and decrease the network lifetime. In this paper, we focus on those injecting traffic attacks launched by insider attackers. After investigating the possible types of injecting traffic attacks, we have proposed two sets of defense mechanisms to combat such attacks. The first set of defense mechanisms is fully distributed, while the second is centralized with decentralized implementation. The detection performance of the proposed mechanisms has also been formally analyzed. Both theoretical analysis and experimental studies have demonstrated that under the proposed defense mechanisms, there is almost no gain to launch injecting traffic attacks from the attacker's point of view

In autonomous mobile ad hoc networks, nodes belong to different authorities and pursue different goals; therefore, cooperation among them cannot be taken for granted. Meanwhile, some nodes may be malicious, whose objective is to damage the network. In this paper, we present a joint analysis of cooperation stimulation and security in autonomous mobile ad hoc networks under a game theoretic framework. We first investigate a simple yet illuminating two-player packet forwarding game and derive the optimal and cheat-proof packet forwarding strategies. We then investigate the secure routing and packet forwarding game for autonomous ad hoc networks in noisy and hostile environments and derive a set of reputation-based cheat-proof and attack-resistant cooperation stimulation strategies. When analyzing the cooperation strategies, besides Nash equilibrium, other optimality criteria, such as Pareto optimality, subgame perfection, fairness, and cheat-proofing, have also been considered. Both analysis and simulation studies have shown that the proposed strategies can effectively stimulate cooperation among selfish nodes in autonomous mobile ad hoc networks under noise and attacks, and the damage that can be caused by attackers is bounded and limited

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by rewarding some payment for cooperative behaviors. Here, we model the pricing and routing in autonomous MANETs as multi-stage dynamic games. A dynamic pricing framework is proposed to maximize the sender/receiver's payoff by considering the dynamic nature of MANETs. Meanwhile, the forwarding incentives of the relay nodes can also be maintained by providing the optimal payments based on the auction rules. The simulation results illustrate that the proposed dynamic pricing schemes have significant performance gains over the existing static pricing algorithms.

The performance of distributed networks depends on collaboration among distributed entities. To enhance security in distributed networks, such as ad hoc networks, it is important to evaluate the trustworthiness of participating entities since trust is the major driving force for collaboration. In this paper, we present a framework to quantitatively measure trust, model trust propagation, and defend trust evaluation systems against malicious attacks. In particular, we address the fundamental understanding of trust, quantitative trust metrics, mathematical properties of trust, dynamic properties of trust, and trust models. The attacks against trust evaluation are identified and defense techniques are developed. The proposed trust evaluation system is employed in ad hoc networks for securing ad hoc routing and assisting malicious node detection. The implementation is fully distributed. Simulations show that the proposed system can significantly improve network throughput as well as effectively detect malicious behaviors in ad hoc networks. Further, extensive simulations are performed to illustrate various attacks and the effectiveness of the proposed defense techniques.

The gains of cooperative communications in wireless networks have been explored recently under the ideal assumption of negligible receiving and processing power. In sensor networks, the power spent for listening and computing can constitute a significant portion of the total consumed power, and such an overhead can reduce the gains promised by cooperation. In this paper, cooperation gains are investigated by taking into consideration such overheads in the analytical framework. The performance metric considered is the energy efficiency of the system measured by the total power required to achieve a certain quality of service requirement. The analytical and numerical results reveal very interesting threshold behavior below which direct transmission is more energy efficient, and above which cooperation provides more gains. Such a tradeoff is shown to depend on many parameters such as the relative locations of the source and destination, the values of the receive and processing powers, the application, and many other factors. Moreover, there are experimental results conducted to verify the channel model assumed in the paper

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, the issue of cooperation enforcement must be solved first to enable network functioning, such as packet forwarding, which becomes very difficult under noise and imperfect monitoring. In this paper, we focus on cooperation enforcement in autonomous mobile ad hoc networks under noise and imperfect observation and study the basic packet-forwarding function using the repeated game models with imperfect information. A belief-based packet forwarding framework is proposed to obtain cooperation-enforcement strategies solely based on each node's own past actions and its private imperfect observation of other nodes' information. The simulation results illustrate that the proposed belief-based packet forwarding approach can enforce the cooperation with only a small performance degradation compared with the unconditionally cooperative outcomes when noise and imperfect observation exist

In self-organized mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. In this paper, we focus on cooperation enforcement in the self-organized mobile ad hoc networks with noise and imperfect observation and study the basic packet-forwarding function using the repeated game models with imperfect information. A belief-based packet forwarding framework is proposed to obtain cooperation-enforcement strategies solely based on each node's own past actions and its private imperfect observation of other nodes' information. The simulation results illustrate that the proposed belief-based packet forwarding approach can enforce the cooperation with only a small performance degradation compared to the unconditionally cooperative outcomes in the ad hoc networks with noise and imperfect observation.

The performance of ad hoc networks depends on cooperation and trust among distributed nodes. To enhance security in ad hoc networks, it is important to evaluate trustworthiness of other nodes without centralized authorities. In this paper, we present an information theoretic framework to quantitatively measure trust and model trust propagation in ad hoc networks. In the proposed framework, trust is a measure of uncertainty with its value represented by entropy. We develop four Axioms that address the basic understanding of trust and the rules for trust propagation. Based on these axioms, we present two trust models: entropy-based model and probability-based model, which satisfy all the axioms. Techniques of trust establishment and trust update are presented to obtain trust values from observation. The proposed trust evaluation method and trust models are employed in ad hoc networks for secure ad hoc routing and malicious node detection. A distributed scheme is designed to acquire, maintain, and update trust records associated with the behaviors of nodes' forwarding packets and the behaviors of making recommendations about other nodes. Simulations show that the proposed trust evaluation system can significantly improve the network throughput as well as effectively detect malicious behaviors in ad hoc networks.

In this paper, we present two new methods for efficient rate control and entropy coding in lossy image compression using JPEG-2000. These two methods enable significant improvements in computation complexity and power consumption over the traditional JPEG-2000 algorithms. First, we propose a greedy heap-based rate-control algorithm (GHRaC), which achieves efficient postcompression rate control by implementing a greedy marginal analysis method using the heap sort algorithm. Second, we propose an integrated rate-control and entropy-coding (IREC) algorithm that reduces the computation complexity of entropy coding by selectively entropy coding only the image data that is likely to be included in the final bitstream, as opposed to entropy coding all image data. Together, these two methods enable significant savings in computation time and power consumption. For example, the GHRaC method demonstrates 16 /spl times/ speedup for rate control when encoding the Lena color image using a target compression ratio of 128:1, one quality layer, and code blocks of 32 /spl times/ 32 pixels. The IREC method expands upon GHRaC to perform entropy coding in conjunction with rate control. Using an enhanced version of IREC, these two methods jointly achieve a speedup in execution time of 14 /spl times/ over traditional rate control and entropy coding, which first entropy codes all image coefficients and then separately performs postcompression rate control using the generalized Lagrange multiplier method to select which data are included in the final bitstream. Both theoretical analysis and empirical results are presented in validating the advantages of the proposed methods.

In self-organized mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by rewarding some payment for cooperative behaviors. In this paper, we model the pricing and routing in self-organized MANETs as multistage dynamic games. A dynamic pricing framework is proposed to maximize the sender/receiver's payoff by considering the dynamic nature of MANETs, meanwhile, keeping the forwarding incentives of the relay nodes by providing the optimal payments based on the auction rules. The simulation results illustrate that the proposed dynamic pricing schemes have significant performance gains over the existing static pricing algorithms.

The performance of ad hoc networks depends on the cooperative and trust nature of the distributed nodes. To enhance security in ad hoc networks, it is important to evaluate the trustworthiness of other nodes without central authorities. In this paper, we present an information theoretic framework to quantitatively measure trust and model trust propagation in ad hoc networks. In the proposed information theoretic framework, trust is a measure of uncertainty with its value represented by entropy. We develop Axioms that address the basic rules for trust propagation. Based on these Axioms, we present two trust models: entropy-based model and probability-based model, which satisfy all the Axioms. The proposed trust evaluation method and trust models are employed in ad hoc networks for secure ad hoc routing and malicious node detection. Simulations show that the proposed framework can significantly improve network throughput as well as effectively detect malicious behaviors in ad hoc networks.

In this paper we investigate how to defend against injecting traffic attacks in cooperative ad hoc networks. By injecting an overwhelming amount of packets into the network, the attackers can easily consume valuable network resources and reduce nodes' lifetime. Since in cooperative ad hoc networks nodes will usually unconditionally forward packets for other nodes, such networks are extremely vulnerable to injecting traffic attacks, especially those launched by inside attackers. In this paper, the possible types of injecting traffic attackers are studied, and a set of mechanisms are proposed to protect cooperative ad hoc network against such attacks. The performance of the proposed mechanisms is analyzed, which show that from attackers' point of view, the best strategy is not to launch injecting traffic attacks. Simulation studies also confirm the theoretical analysis.

In self-organized ad hoc networks, nodes usually belong to different authorities and pursue different goals. To save their valuable resources, they tend to be selfish. Meanwhile, some nodes may be malicious whose objective is to degrade the network performance. In this paper, we present an anti-attack cooperation stimulation system for self-organized ad hoc networks to stimulate cooperation among selfish nodes and to defend against attacks. In the proposed system, the damage that can be caused by attackers is bounded, and the cooperation among selfish nodes is enforced. Simulation studies also verify the effectiveness of the proposed system. Another key property of the proposed system is that it is fully distributive, and does not require any tamper-proof hardware or central management point.

While contributory group key agreement is a promising solution to achieve access control in collaborative and dynamic group applications, the existing schemes have not achieved the performance lower bound in terms of rekeying overhead. In this paper we introduce a contributory group key agreement that achieves the performance lower bound by utilizing a novel logical key tree structure, called PFMH, and the concept of phantom user position. In particular, the proposed scheme only needs O(1) rounds of two-party Diffie-Hellman upon any single user join event and O(log n) rounds of two-party Diffie-Hellman upon any single user leave event. Both theoretical bound analysis and simulation studies show that the proposed scheme achieves much lower rekeying cost than the existing tree-based contributory group key agreement schemes.

HADOF is a set of mechanisms to protect mobile ad hoc networks against routing disruption attacks launched by inside attackers. First, each node launches a route traffic observer to monitor the behavior of each valid route in its route cache, and to collect the packet forwarding statistics submitted by the nodes on this route. Since malicious nodes may submit false reports, each node also keeps cheating records for other nodes. If a node is detected as dishonest, this node will be excluded from future routes, and the other nodes will stop forwarding packets for it. Third, each node will try to build friendship with other nodes to speed up malicious node detection. Route diversity will be explored by each to discover multiple routes to the destination, which can increase the chance of defeating malicious nodes who aim to prevent good routes from being discovered. In addition, adaptive route rediscovery will be applied to determine when new routes should be discovered. HADOF can handle various attacks and introduces little overhead to the existing protocols. Both analysis and simulation studies have confirmed the effectiveness of HADOF.

We investigate how to defend against injecting traffic attacks in cooperative mobile ad hoc networks where nodes belong to the same authority and pursue the common goals. By injecting an overwhelming amount of traffic into the network, the attackers can easily consume good nodes' valuable network resources and reduce the network's lifetime. Since in cooperative mobile ad hoc networks nodes will usually unconditionally forward packets for other nodes, such networks are extremely vulnerable to injecting traffic attacks, especially those launched by inside attackers. In this paper, the possible types of injecting traffic attackers are studied, and a set of mechanisms are proposed to protect cooperative mobile ad hoc network against such attacks. The performance of the proposed mechanisms is analyzed. Both theoretical and experimental bounds are derived, which show that from attackers' point of view, the best strategy is not to launch injecting traffic attacks. Simulation studies have also verified the theoretical analysis.

In self-organized mobile ad hoc networks, nodes belong to different authorities and pursue different goals, so they tend to be selfish, that is, they try to maximize the benefits they can get from the network, but are not willing to forward packets for the benefits of other nodes. Meanwhile, some nodes may be malicious whose objective is to degrade the network's performance and waste other nodes' valuable resource. Here we propose an Attack-Resilient Cooperation Stimulation (ARCS) system for self-organized mobile ad hoc networks to stimulate cooperation among selfish nodes and to defend against attacks. In the ARCS system, the damage that can be caused by malicious nodes is bounded, and the cooperation among selfish nodes is enforced. Both theoretical analysis and simulation studies have confirmed the effectiveness of the ARCS system. Another key property of the ARCS system lies in that it is completely self-organizing and fully distributed, and does not require any tamper-proof hardware or central management points.

In autonomous ad hoc networks, nodes usually belong to different authorities and pursue different goals. In order to maximize their own performance, nodes in such networks tend to be selfish, and are not willing to forward packets for the benefits of other nodes. Meanwhile, some nodes might behave maliciously and try to disrupt the network and waste other nodes' resources. In this paper, we present an attack-resilient cooperation stimulation (ARCS) system for autonomous ad hoc networks to stimulate cooperation among selfish nodes and defend against malicious attacks. In the ARCS system, the damage that can be caused by malicious nodes can be bounded, the cooperation among selfish nodes can be enforced, and the fairness among nodes can also be achieved. Both theoretical analysis and simulation results have confirmed the effectiveness of the ARCS system. Another key property of the ARCS system lies in that it is completely self-organizing and fully distributed, and does not require any tamper-proof hardware or central management points.

In this paper we study the bit allocation problem under multiple rate constraints. This problem has been arisen in many practical situations, such as optimal image and video quantization, buffer-constrained multimedia transmission, joint source channel coding and unequal error protection. To solve the bit allocation problem under both total rate budget and maximum buffer size constraints, Lagrangian-based iterative technique can be used. The bit allocation problem are reexamined in this paper under multiple rate constraints, and propose an efficient algorithm based on marginal analysis to solve the rate-distortion optimization problem under both rate and buffer constraints. The paper has used optimal quantization and joint source channel coding based rate allocation.

In this paper, we present an integrated rate control and entropy coding (IREC) scheme for JPEG 2000. Based on an efficient heap-based rate allocation algorithm, the characteristics of image content, the subband coefficient and bitplane weighting models, and the user-specified optimization criteria, the proposed IREC scheme can selectively perform entropy coding only on those parts of image data that are likely to be included in the final bitstream. Since entropy coding is the most time and power consuming part, the IREC scheme can then reduce the overall computation and power consumption of JPEG 2000 encoding procedure. Both theoretical analysis and empirical results validate the advantages of the IREC scheme. For example, when encoding the Lenna color image with a targeted compression ratio of 128:1, compared with the separate rate control and entropy coding schemes, about 93% savings in computation and power consumption can be achieved on the entropy coding procedure.

We present an efficient real-time JPEG 2000 image transmission system over heterogeneous wireless networks. By exploiting the advantages of the UDP-lite protocol and cross-layer optimization, the system can utilize the limited bandwidth more efficiently. Moreover, a scalable cross-layer rate allocation (SCRA) algorithm is proposed to perform the cross-layer optimization. The algorithm can manage a large number of adjustable parameters with low complexity. The simulation results show that by using the proposed method, 1.5 dB gain in PSNR can be obtained for a fixed transmission rate of 0.5 bpp, or 30% transmission time can be saved under an end-to-end distortion constraint of 30 dB in PSNR.

This paper presents a hierarchical image representation that preserves spatial relationships, and an image segmentation algorithm that efficiently constructs this representation. The overall structure of the hierarchical representation assumes a tree-like organization, in which a node at a higher level represents of a group of nodes from the next lower level. The root node of the representation is the full image, and the leaf nodes are K /spl times/ K blocks of pixels (usually 4 /spl times/ 4 or 8 /spl times/ 8), called blobs. The segmentation algorithm builds this hierarchical representation using an efficient clustering algorithm for grouping nodes progressively into larger objects. While performing the union of nodes at one level into a single parent node at the next higher level of the tree, nodes are grouped together according to similarities between their feature vectors, which include such features as color information, orientation, texture, size, energy, and neighbor information. The computation complexity of the hierarchical image segmentation algorithm is O(MN + MN/K/sup 2/ log(MN/K/sup 2/)), where M, N are the height and width of the original image. Experimental results show that this algorithm can segment images and extract objects effectively.