Fair bandwidth sharing in distributed systems: a game-theoretic approach

Rakshit, Sudipta; Guha, Ratan K.

doi:10.1109/tc.2005.183

Cited by 22 publications

(1 citation statement)

References 36 publications

(31 reference statements)

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“…Such requests task allocation scheme of the system can dynamically respond to these changes, and timely completion of assignment; ont the other hand the ability of each member of the system constantly changing dynamicly may cause assigned task can not be completed timely or the load of the system is not balance, in order to improve the completion of the task successfully ,It need to assign these tasks again. Game theory [3][4][5][6][7][8][9] has been widely used in the task assigned, on the basis of previous studies, this paper will use game theory methods to achieve dynamic task allocation.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Task Allocation Based on Game Theory

Wan

2014

AMR

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Multi-Agent System for task allocation problem, the introduction of game theory for dynamic task allocation modeling Multi-Agent Systems,Multi-Agent System proposed dynamic task allocation algorithm based on game theory.Experimental results show that the lower complexity of dynamic task allocation algorithm based on game theory in this article, the smaller amount of calculation,better robustness,task allocation scheme to obtain higher quality,with higher distribution

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Section: Introductionmentioning

confidence: 99%

Dynamic Task Allocation Based on Game Theory

Wan

2014

AMR

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Distributed self‐organizing bandwidth allocation for priority‐based bus communication

Ziermann

Wildermann

Mühleis

et al. 2011

Concurrency and Computation

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The raising complexity in distributed embedded systems makes it necessary that the communication of such systems organizes itself automatically. In this paper, we tackle the problem of sharing bandwidth on priority-based buses. Based on a game theoretic model, reinforcement learning algorithms are proposed that use simple local rules to establish bandwidth sharing. The algorithms require little computational effort and no additional communication. Extensive experiments show that the proposed algorithms establish the desired properties without global knowledge or a priori information. It is proven that communication nodes using these algorithms can co-exist with nodes using other scheduling techniques. Finally, we propose a procedure that helps to set the learning parameters according to the desired behavior. Therefore, we prefer to approach the goal of a working communication system from a different perspective. Starting with minimal constraints on the individual communication nodes, the nodes themselves should be able to establish communication. This should be done by using simple local rules with as less global information as possible. As the first step in this development process, we want to take a look at bandwidth-constrained communication, where the quality of the function varies with the used amount of bandwidth. In future work, these constraints will be extended to cover a larger field of applications.The remainder of the paper is organized as follows. In Section 2 the problem is defined and placed into the context-related work. In Section 3, the priority-based medium access game is formulated, which represents the fundamentals for the proposed methods. Section 4 presents the distributed reinforcement learning algorithm to establish fair bandwidth distribution. The parameters are analyzed and it is proven that the algorithm also works together with other scheduling methods. In Section 5, the period access scheme is introduced and analyzed, while Section 6 concludes our work and gives outlook on future work.

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