Game theoretic power aware wireless data access

The paper examines the following wireless data access scenario: a number of clients are interested in a set of data items kept at the server. A client sends a query request to inform the server of its desired data item. The server replies in the common broadcast channel. We first define a utility function that considers the client's power consumption in transmit, receive and idle modes. Specifically, utility is expressed as the number of queries that can be completed given a fixed energy source. Based on the utility function, we formulate our power aware wireless data access scheme as a non-cooperative game, called the WDA game. From our theoretical analysis, we show that clients are not always necessary to send query requests to the server. Instead, each client determines the request probability without any explicit communication with one another. Furthermore, we design and evaluate the server and client algorithms for the WDA game. Simulation results confirm that our proposed scheme, compared with a simple always-request one, increases the utility and lifetime of every client while reducing the number of requests sent, at the cost of a slightly larger average query delay.published_or_final_versio

On game theoretic peer selection for resilient peer-to-peer media streaming

Peer-to-peer (P2P) media streaming quickly emerges as an important application over the Internet. A plethora of approaches have been suggested and implemented to support P2P media streaming. In our study, we first classified existing approaches and studied their characteristics by looking at three important quantities: number of upstream peers (parents), number of downstream peers (children), and average number of links per peer. In existing approaches, peers are assigned with a fixed number of parents without regard to their contributions, measured by the amount of outgoing bandwidths. Obviously, this is an undesirable arrangement as it leads to highly inefficient use of the P2P links. This observation motivates us to model the peer selection process as a cooperative game among peers. This results in a novel peer selection protocol such that the number of upstream peers of a peer is related to its outgoing bandwidth. Specifically, peers with larger outgoing bandwidth are given more parents, which make them less vulnerable to peer dynamics. Simulation results show that the proposed protocol improves delivery ratio using similar number of links per peer, comparing with existing approaches under a wide range of system parameters. © 2009 IEEE.published_or_final_versio

Game-Theoretic Optimal Power-Link Quality Topology Control in Wireless Sensor Networks

One of the most significant problems in Wireless Sensor Network (WSN) deployment is the generation of topologies that maximize transmission reliability and guarantee network connectivity while also maximizing the network’s lifetime. Transmission power settings have a large impact on the aforementioned factors. Increasing transmission power to provide coverage is the intuitive solution yet with it may come with lower packet reception and shorter network lifetime. However, decreasing the transmission power may result in the network being disconnected. To balance these trade-offs we propose a discrete strategy game-theoretic solution, which we call TopGame that aims to maximize the reliability between nodes while using the most appropriate level of transmission power that guarantees connectivity. In this paper, we provide the conditions for the convergence of our algorithm to a pure Nash equilibrium as well as experimental results. Here we show, using the Indriya WSN testbed, that TopGame is more energy-efficient and approaches a similar packet reception ratio with the current closest state of the art protocol ART. Finally, we provide a methodology for further optimization of our work using an indicator function to distinguish between satisfactory and poor links

Optimization and Learning in Energy Efficient Cognitive Radio System

Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized. Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless systems that they can adapt their operating parameters, i.e. transmission power, channel, modulation according to the surrounding radio environment to explore the opportunity. In this dissertation, the study is focused on the optimization and learning of energy efficiency in the cognitive radio system, which can be considered to better utilize both the energy and spectrum resources. Firstly, drowsy transmission, which produces optimized idle period patterns and selects the best sleep mode for each idle period between two packet transmissions through joint power management and transmission power control/rate selection, is introduced to cognitive radio transmitter. Both the optimal solution by dynamic programming and flexible solution by reinforcement learning are provided. Secondly, when cognitive radio system is benefited from the theoretically infinite but unsteady harvested energy, an innovative and flexible control framework mainly based on model predictive control is designed. The solution to combat the problems, such as the inaccurate model and myopic control policy introduced by MPC, is given. Last, after study the optimization problem for point-to-point communication, multi-objective reinforcement learning is applied to the cognitive radio network, an adaptable routing algorithm is proposed and implemented. Epidemic propagation is studied to further understand the learning process in the cognitive radio network

A game theoretic approach to power aware wireless data access

We consider a basic scenario in wireless data access: a number of mobile clients are interested in a set of data items kept at a common server. Each client independently sends requests to inform the server of its desired data items and the server replies with a broadcast channel. We are interested in studying the energy consumption characteristics in such a scenario. First, we define a utility function for quantifying performance. Based on the utility function, we formulate the wireless data access scenario as a noncooperative game - wireless data access (WDA) game. Although our proposed probabilistic data access scheme does not rely on client caching, game theoretical analysis shows that clients do not always need to send requests to the server. Simulation results also indicate that our proposed scheme, compared with a simple always-request one, increases the utility and lifetime of every client while reducing the number of requests sent, with a cost of slightly larger average query delay. We also compare the performance of our proposed scheme with two popular schemes that employ client caching. Our results show that caching-only benefits clients with high query rates at the expense of both shorter lifetime and smaller utility in other clients. © 2006 IEEE.published_or_final_versio