Price-Based Optimal Resource Allocation in Multi-Hop Wireless Networks

Recent advances in wireless communications and digital electronics have enabled rapid development of a variety of wireless network technologies. The undeniable popularity of wireless network is due to its ubiquity and convenience, which is appreciated by the users. In this dissertation, we study the problem of resource allocation in multihop wireless networks (so called ad hoc networks). A wireless ad hoc network consists of a collection of wireless nodes without a fixed infrastructure. Two wireless nodes communicate with each other directly, if they are within the transmission range of each other. Otherwise, the communication is achieved through the relays of intermediate nodes. Compared with traditional wireline networks, the unique characteristics of wireless networks pose fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair across different network flows. Particularly, the following issues of wireless networks need fresh treatment: (1) Interference of wireless communication. Flows not only contend at the same node (contention in the time domain), but also compete for shared channel if they are within the interference ranges of each other (contention in the spatial domain). (2) Multiple resource usage. Sending data from one wireless node to another needs to consume multiple resources, most notably wireless bandwidth and battery energy. (3) Autonomous communication entities. The wireless nodes usually belong to different autonomous entities. They may lack the incentive to contribute to the network functionality in a cooperative way. (4) Rate diversity. Wireless nodes can adaptively change the transmission bit rate based on perceived channel conditions. This leads to a wireless network with rate diversity, where competing flows within the interference range transmit at different rates. None of the existing resource allocation algorithms in wireless ad hoc networks have realistically considered end-to-end flows spanning multiple hops. Moreover, strategies proposed for wireline networks are not applicable in the context of wireless ad hoc network, due to its unique characteristics. In this dissertation, we propose a new price-based resource allocation framework in wireless ad hoc networks to achieve optimal resource utilization and fairness among competing end-to-end flows. We build our pricing framework on the notion of maximal cliques in wireless ad hoc networks, as compared to individual links in traditional wide-area wireline networks. Based on such a price-based theoretical framework, we present a two-tier iterative algorithm. Distributed across wireless nodes, the algorithm converges to a global network optimum with respect to resource allocations. Further, we present a price pair mechanism to coordinate multiple resource allocations, and to provide incentives simultaneously such that cooperation is promoted and the desired global optimal network operating point is reached by convergence with a fully decentralized self-optimizing algorithm. Such desired network-wide global optimum is characterized with the concept of Nash bargaining solution, which not only provides the Pareto optimal point for the network, but is also consistent with the fairness axioms of game theory. Finally, we present a channel aware price generation scheme to decompose the bit rate adjustment and the flow rate allocation. The allocation result achieves channel time fairness where user fairness and channel utilization is balanced. The major achievements of this dissertation are outlined as follows. It models a system-wide optimal operation point of a wireless network, and outlines the solution space of resource allocation in a multihop wireless network; It presents a price-based distributed resource allocation algorithm to achieve this global optimal point; It presents a low overhead implementation of the price-based resource allocation algorithm; It presents an incentive mechanism that enables the resource allocation algorithm when users are selfish

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

A Fair and Secure Cluster Formation Process for Ad Hoc Networks

An efficient approach for organizing large ad hoc networks is to divide the nodes into multiple clusters and designate, for each cluster, a clusterhead which is responsible for holding intercluster control information. The role of a clusterhead entails rights and duties. On the one hand, it has a dominant position in front of the others because it manages the connectivity and has access to other node¿s sensitive information. But on the other hand, the clusterhead role also has some associated costs. Hence, in order to prevent malicious nodes from taking control of the group in a fraudulent way and avoid selfish attacks from suitable nodes, the clusterhead needs to be elected in a secure way. In this paper we present a novel solution that guarantees the clusterhead is elected in a cheat-proof manner

Observation-based Cooperation Enforcement in Ad Hoc Networks

Ad hoc networks rely on the cooperation of the nodes participating in the network to forward packets for each other. A node may decide not to cooperate to save its resources while still using the network to relay its traffic. If too many nodes exhibit this behavior, network performance degrades and cooperating nodes may find themselves unfairly loaded. Most previous efforts to counter this behavior have relied on further cooperation between nodes to exchange reputation information about other nodes. If a node observes another node not participating correctly, it reports this observation to other nodes who then take action to avoid being affected and potentially punish the bad node by refusing to forward its traffic. Unfortunately, such second-hand reputation information is subject to false accusations and requires maintaining trust relationships with other nodes. The objective of OCEAN is to avoid this trust-management machinery and see how far we can get simply by using direct first-hand observations of other nodes' behavior. We find that, in many scenarios, OCEAN can do as well as, or even better than, schemes requiring second-hand reputation exchanges. This encouraging result could possibly help obviate solutions requiring trust-management for some contexts.Comment: 10 pages, 7 figure

Cooperative smartphone relay selection based on fair power utilization for network coverage extension

This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain's fairness index and utility of end devices in both symmetric and asymmetric network configurations