Distributed Joint Rate and Power Control Game-Theoretic Algorithms for Wireless Data

Hayajneh, Mohammad; Abdallah, Chaouki T.

doi:10.1109/lcomm.2004.833817

Cited by 57 publications

(51 citation statements)

References 7 publications

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“…This function is known as a potential function and, generally, it is a real-valued function on the joint strategy space (the Cartesian product of all agents' strategy spaces), defined such that the change in a unilaterally deviating player's utility is matched by the change in the potential function. The class of finite potential games have been used to describe many problems in multi-agent systems, in particular congestion problems on networks [35], and more recently, power control, channel selection and scheduling problems in wireless networks [14,15], target assignment problems [4] and job scheduling [48].…”

Section: Potential Gamesmentioning

confidence: 99%

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Benchmarking hybrid algorithms for distributed constraint optimisation games

Chapman

Rogers

Jennings

2010

Auton Agent Multi-Agent Syst

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In this paper, we consider algorithms for distributed constraint optimisation problems (DCOPs). Using a potential game characterisation of DCOPs, we decompose eight DCOP algorithms, taken from the game theory and computer science literatures, into their salient components. We then use these components to construct three novel hybrid algorithms. Finally, we empirical evaluate all eleven algorithms, in terms of solution quality, timeliness and communication resources used, in a series of graph colouring experiments. Our experimental results show the existence of several performance trade-offs (such as quick convergence to a solution, but with a cost of high communication needs), which may be exploited by a system designer to tailor a DCOP algorithm to suit their mix of requirements.

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Section: Potential Gamesmentioning

confidence: 99%

“…[14,15,18]), industrial task allocation and scheduling problems (e.g. [40,48]), and the management of congested air, road, rail, and information networks (e.g.…”

mentioning

confidence: 99%

Benchmarking hybrid algorithms for distributed constraint optimisation games

Chapman

Rogers

Jennings

2010

Auton Agent Multi-Agent Syst

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“…An approach to adjust the transmission power of a node in WSN is based on game theory which has its roots in economics [6] and there has been a growing interest in applying game theory to study wireless systems [7][8][9]. Game theory involves a set of competing players looking to maximize their own utility, based upon certain actions they can take.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Modulation and Coding for Utility Enhancement in VMIMO WSN Using Game Theory

Valli¹,

Dananjayan²

2013

IJCTE

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Abstract-The primary component of resource management in wireless sensor network (WSN) is transmitter power control since the sensors are tiny, low cost battery powered devices. The adverse impacts caused by radio irregularities and fading increase the energy consumption and thereby reduce the WSN lifetime. An efficient power control technique is important to sustain system quality and efficiency of wireless sensor networks in such fading conditions. To reduce the fading effects in wireless channel, multi-input multi-output (MIMO) scheme is utilised for sensor network. This paper proposes a power control solution for Virtual MIMO (VMIMO) WSN using game theoretic approach. The game is formulated as a utility maximizing distributed power control game in VMIMO WSN considering the residual energy of the nodes along with adaptive modulation. The proposed algorithm adapts to the changes in channel condition and selects the appropriate modulation and transmits using the optimal transmission power. Simulation results show that the game with pricing provides maximum utility by consuming lesser power.

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“…In recent years there has been a growing interest in applying game theory to study wireless systems. [6], [7] used game theory to investigate power control and rate control for wireless data. In [8], the authors provide motivations for using game theory to study communication systems, and in particular power control.…”

Section: Introductionmentioning

confidence: 99%