Game theoretic approach in routing protocol for wireless ad hoc networks

This paper introduces a game theoretic method, called forwarding dilemma game (FDG), which controls routing overhead in dense multi-hop wireless ad hoc networks. The players of the game are the wireless nodes with set of strategies {Forward, Not forward}. The game is played whenever an arbitrary node in the network receives a flooding packet. In FDG, every player needs to know the number of players of the game. That is why a neighbor discovery protocol (NDP) is introduced. In order for NDP to function, a field is attached to the flooding packets (routing overhead packets). The mixed strategy Nash equilibrium is used as a solution for the FDG. This provides the probability that the flooding packet would be forwarded by the receiver node. FDG with NDP is implemented in AODV protocol in Network Simulator NS-2 to verify its performance with simulations. FDG with NDP improves performance of the AODV compared to the same network with only AODV protocol in moderate and high node densities. FDG can be applied to any routing protocol that uses flooding in the route discovery phase

Adaptive resource allocation for cognitive wireless ad hoc networks

Widespread use of resource constrained wireless ad hoc networks requires careful management of the network resources in order to maximize the utilization. In cognitive wireless networks, resources such as spectrum, energy, communication links/paths, time, space, modulation scheme, have to be managed to maintain quality of service (QoS). Therefore in the first paper, a distributed dynamic channel allocation scheme is proposed for multi-channel wireless ad hoc networks with single-radio nodes. The proposed learning scheme adapts the probabilities of selecting each channel as a function of the error in the performance index at each step. Due to frequent changes in topology and flow traffic over time, wireless ad hoc networks require a dynamic routing protocol that adapts to the changes of the network while allocating network resources. In the second paper, approximate dynamic programming (ADP) techniques are utilized to find dynamic routes, while solving discrete-time Hamilton-Jacobi-Bellman (HJB) equation forward-in-time for route cost. The third paper extends the dynamic routing to multi-channel multi-interface networks which are affected by channel uncertainties and fading channels. By the addition of optimization techniques through load balancing over multiple paths and multiple wireless channels, utilization of wireless channels throughout the network is enhanced. Next in the fourth paper, a decentralized game theoretic approach for resource allocation of the primary and secondary users in a cognitive radio networks is proposed. The priorities of the networks are incorporated in the utility and potential functions which are in turn used for resource allocation. The proposed game can be extended to a game among multiple co-existing networks, each with different priority levels --Abstract, page iv

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 Non-Cooperative Game Theoretical Approach For Power Control In Virtual MIMO Wireless Sensor Network

Power management is one of the vital issue in wireless sensor networks, where the lifetime of the network relies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes and the network. One efficient way of power management is to control the power at which the nodes transmit. In this paper, a virtual multiple input multiple output wireless sensor network (VMIMO-WSN)communication architecture is considered and the power control of sensor nodes based on the approach of game theory is formulated. The use of game theory has proliferated, with a broad range of applications in wireless sensor networking. Approaches from game theory can be used to optimize node level as well as network wide performance. The game here is categorized as an incomplete information game, in which the nodes do not have complete information about the strategies taken by other nodes. For virtual multiple input multiple output wireless sensor network architecture considered, the Nash equilibrium is used to decide the optimal power level at which a node needs to transmit, to maximize its utility. Outcome shows that the game theoretic approach considered for VMIMO-WSN architecture achieves the best utility, by consuming less power.Comment: 12 pages, 8 figure

Game theoretic approach in routing protocols for wireless mobile ad hoc networks

Mobile Ad hoc Networks (MANETs) are becoming popular as a means of providing communication among a group of people. Because of self-configuring and self-organizing characteristics, MANETs can be deployed quickly. There is no infrastructure defined in the network, therefore all of the participating nodes relay packets for other nodes and perform routing if necessary. Because of the limitations in wireless transmission range, communication links could be multi-hop. Routing protocol is the most important element of MANET. Routing protocols for MANET can broadly be classified as proactive routing protocol and reactive routing protocol. In proactive routing protocols like Destination Sequence Distance Vector (DSDV), mobile nodes periodically exchange routing information among themselves. Hence proactive routing protocols generate high overhead messages in the network. On the other hand, reactive routing protocols like Ad hoc On-demand Distance Vector (AODV) and Dynamic Source Routing (DSR) work on-demand. Hence reactive routing protocols generate fewer number of overhead messages in the network compared to proactive routing protocols. But reactive routing protocols use a global search mechanism called flooding during the route discovery process. By flooding mechanism a source node can discover multiple routes to a destination. Flooding generates a large number of overhead packets in the network and is the root cause of scaling problem of reactive routing protocols. Hierarchical Dynamic Source Routing (HDSR) protocol has been proposed in this dissertation to solve that scaling problem. The DSR protocol has been modified and optimized to implement HDSR protocol. HDSR protocol reduces the flooding problem of reactive routing protocols by introducing hierarchy among nodes. Two game theoretic models, Forwarding Dilemma Game (FDG) and Forwarding Game Routing Protocol (FGRP), is proposed to minimize the \u27flooding\u27 effect by restricting nodes that should participate in route discovery process based on their status. Both FDG and FGRP protocols reduce overhead packet and improve network performances in terms of delay packet delivery ratio and throughput. Both protocols were implemented in AODV and the resulting protocol outperformed AODV in our NS-2 simulations. A thorough connectivity analysis was also performed for FDG and FGRP to ensure that these protocols do not introduce disconnectivity. Surprisingly, both FDG and FGRP showed better connectivity compared to AODV in moderate to high node density networks