A potential game approach to distributed power control and scheduling

Heikkinen, Tiina

doi:10.1016/j.comnet.2005.09.010

Cited by 97 publications

(66 citation statements)

References 30 publications

(111 reference statements)

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“…3 Alongside this and other work that has been applied in the RoboCup Rescue simulator, 4 ALADDIN Project researchers have also applied MAS-based techniques to the closely-related problem of industrial task allocation [6], evacuation scenarios [2] and distributed sensor management [34,3]. Research has also been carried out on fundamental problems that arise in MAS design, including research into algorithms for distributed constraint optimisation problems (such as the Distributed Stochastic Algorithm used in this paper) [35], models of congestion in common-resource usage games [7] and coalition formation problems [33,36].…”

Section: Related Workmentioning

confidence: 98%

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Decentralized Dynamic Task Allocation Using Overlapping Potential Games

Chapman

Micillo

Kota

et al. 2010

The Computer Journal

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This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a stochastic game formulation of these problems in which tasks have varying hard deadlines and processing requirements. We then introduce a new technique for approximating this game using a series of static potential games, before detailing a decentralised method for solving the approximating games that uses the distributed stochastic algorithm. Finally, we discuss an implementation of our approach to a task allocation problem in the RoboCup Rescue disaster management simulator. The results show that our technique performs comparably to a centralised task scheduler (within 6% on average), and also, unlike its centralised counterpart, it is robust to restrictions on the agents' communication and observation ranges.

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Section: Related Workmentioning

confidence: 98%

“…[1,2]), wide-area surveillance and distributed sensor network management (e.g. [3,4]), industrial task allocation and scheduling problems (e.g. [5,6]), and in the control and management of congestion within air, road, rail, and information networks (e.g.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Dynamic Task Allocation Using Overlapping Potential Games

Chapman

Micillo

Kota

et al. 2010

The Computer Journal

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“…By Lemma 3, best response updates of randomly selected agents converge to a Nash equilibrium. In a similar way, if ∂SW ∂yij > 0 ( ∂SW ∂yij < 0), then y ij = 1 (y ij = 0) to maximize the social welfare given by (11).…”

Section: A Pure Nash Equilibriummentioning

confidence: 99%

Incentives and Resource Sharing in Spectrum Commons

Bae

Beigman

Berry

et al. 2008

2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks

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Abstract-It has been suggested that light regulation in the form of etiquette protocols, device design and bargaining amongst users will suffice to mitigate a tragedy of the commons in unlicensed spectrum. In this paper we propose a game theoretic model to examine this claim. In this game, each user decides whether or not to set up an access point, which operates on a particular (single) band. The effect of regulation is modeled in reduced form through transfers. A user who sets up an access point, provides payments to each neighbor who does not and suffers a disutility depending on the number of interfering access points. A user who does not set up an access point, receives payments from each neighbor that does. For a suitable model of payoffs, the game is a potential game and best response updates converge to a Nash equilibrium of the game. For any interference parameters, there is a suitable transfer resulting in a Nash equilibrium which is efficient. However, all Nash equilibria may not be efficient.

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“…(19) shows that each link only needs to measure its own SINR, which does not need to any message passing among the links. Eq.…”

Section: Remarkmentioning

confidence: 99%

“…Therefore, to deploy an ad hoc network successfully in a self-organized manner, the issue of cooperation stimulation should be solved. Most of the existing works rely on a pricing mechanism as an incentive to a certain degree to facilitate cooperation among self-interested users in power control for cellular systems [2], [3], [18], [25], [30], [38], and ad hoc networks [19], [22]. However, such a pricing mechanism is often difficult to configure and implement in ad hoc networks, since there lacks a central controller or/and there is no single creditable node in wireless ad hoc networks.…”

mentioning

confidence: 99%

Non-cooperative power control for wireless ad hoc networks with repeated games

Long

Zhang

et al. 2007

IEEE J. Select. Areas Commun.

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Abstract-One of the distinctive features in a wireless ad hoc network is lack of any central controller or single point of authority, in which each node/link then makes its own decisions independently. Therefore, fully cooperative behaviors, such as cooperation for increasing system capacity, mitigating interference for each other, or honestly revealing private information, might not be directly applied. It has been shown that power control is an efficient approach to achieve quality of service (QoS) requirement in ad hoc networks. However, the existing work has largely relied on cooperation among different nodes/links or a pricing mechanism that often needs a third-party involvement. In this paper, we aim to design a non-cooperative power control algorithm without pricing mechanism for ad hoc networks. We view the interaction among the users' decision for power level as a repeated game. With the theory of stochastic fictitious play (SFP), we propose a reinforcement learning algorithm to schedule each user's power level. There are three distinctive features in our proposed scheme. First, the user's decision at each stage is self-incentive with myopic best response correspondence. Second, the dynamics arising from our proposed algorithm eventually converges to pure Nash Equilibrium (NE). Third, our scheme does not need any information exchange or to observe the opponents' private information. Therefore, this proposed algorithm can safely run in a fully selfish environment without any additional pricing and secure mechanism. Simulation study demonstrates the effectiveness of our proposed scheme.

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A potential game approach to distributed power control and scheduling

Cited by 97 publications

References 30 publications

Decentralized Dynamic Task Allocation Using Overlapping Potential Games

Decentralized Dynamic Task Allocation Using Overlapping Potential Games

Incentives and Resource Sharing in Spectrum Commons

Non-cooperative power control for wireless ad hoc networks with repeated games

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