分布式环境中基于市场机制的资源自适应调价策略

doi:10.11959/j.issn.1000-436x.2016027

Abstract

Abstract:

To solve the resource pricing problem of the collision among resource utilization, price and benefits in distributed computing environments, a self-adaptive pricing strategy of resource services based on market mechanism was proposed. On the premise of the local resource benefits, this adaptive pricing strategy guaranteed the resource to self-adapt the price dynamically so as to balance the collision between the assigned tasks on the resource node and the benefits of the resource provider. The theoretical ana is proved the effectiveness of the pricing strategy, and the algorithm of the pricing strategy was designed. Resources information in the real distributed systems was used as the performance parameters of experimental node in the sim lation experiments, and the performance of the adaptive pricing strategy was tested in a large-scale grid mission. Experimental results show that, compared with the traditional pricing strategies, the adaptive pricing strategy based on market mechanism has vastly superior performance on the resource benefits and the balance of resource utilization.

Key words: distributed computing, market mechanism, self-adaptive, price adjustment strategy

Chang-song DING,Zhi-ying WANG,Zhi-gang HU. Self-adaptive price adjustment strategy based on market mechanism in distributed environment[J]. Journal on Communications, 2016, 37(2): 32-38.

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References 25

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ID	Grid站点	处理器数量	平均处理能力/GHz
1	Grenoble	232	2.34
2	lille	148	2.67
3	lyon	206	2.37
4	nancy	336	2.50
5	rennes	346	2.18
6	sophia	190	2.44
7	Toulouse	280	2.6

策略	完成时间/s	DX	总利润	总收益
A³PS	411.068	0.000 5	1 140 092	1 461 245
CMM	415.768	0.048 39	854 622	1 174 106
TCM	434.319	0.056 23	685 878	942 282

参数设置	调节次数	完成时间/s	DX	总利润	总收益
μ₁=0.10,μ₂=1.2	94	416.43	0.000 46	1 156 439	1 477 672
μ₁=0.05,μ₂=1.2	180	411.06	0.000 471	1 140 092	1 461 245
μ₁=0.05,μ₂=1.1	185	411.06	0.000 471	1 140 092	1 461 245
μ₁=0.02,μ₂=1.1	448	411.07	0.000 472	1 136 823	1 457 960

Self-adaptive price adjustment strategy based on market mechanism in distributed environment

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