基于半马尔可夫决策过程的媒体服务自适应资源分配

Hongbin Liang, L. Cai, Hangguan Shan, Xuemin Shen, D. Peng
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引用次数: 6

摘要

本文研究了面向服务网络中弹性媒体业务的自适应资源分配问题。我们将资源分配问题建立为一个半马尔可夫决策过程(SMDP),以捕捉用户到达和离开的动态。以网络资源为基础,通过在网络效用和网络资源成本之间取得平衡,做出系统整体回报最大化的最优决策。我们进一步从服务阻塞概率和资源分配的不同决策或动作的概率两方面分析了网络性能。大量的仿真表明,与贪婪资源分配相比,我们提出的方案可以获得更高的网络效用和更低的服务阻塞概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive resource allocation for media services based on semi-Markov decision process
In this paper, we study adaptive resource allocation for elastic media services in service-oriented network. We form ulate the resource allocation problem as a semi-Markov decision process (SMDP) to capture the dynamics of user arrivals and departures. Based on the network resources, an optimal decision is made to maximize the overall system rewards by striking the balance between the network utilities and costs of network resources. We further analyze the network performance in terms of the service blocking probability, and the probability of different decisions or actions of resource allocation. Extensive simulations demonstrate that our proposed scheme can achieve much higher network utility and lower service blocking probability compared with a greedy resource allocation.
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