A DHT and MDP-based mobility management scheme for large-scale mobile internet

Yujia Zhai, Yue Wang, I. You, Jian Yuan, Yong Ren, X. Shan
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引用次数: 19

Abstract

Scalable mobility support is an important task in large-scale mobile Internet. A considerable amount of research on distributed hash table (DHT) based mobility support schemes, which are highly user scalable and load balanced, has been done. However these schemes have shortcomings in query and update performances and network scalability. It is because although routing of overlay itself is effective, there is inconsistency between logical and physical topologies, so the actual physical network performances are not necessarily efficient. In this article, while modeling the overlay mapping query to a Markov decision process (MDP), we define the reward function combining physical layer information with application layer information. Then we present a Markov decision routing (MDR) algorithm, which improves backward induction to get the global optimal strategy, and can balance the complexity of the time and space.We propose a DHT and MDR-based mobility management (DMDRMM) scheme. The numerical results show that the scheme inherits the advantages of the DHT-based management structure, and optimizes the update and query performances of dDHT especially for large-scale network.
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基于DHT和mdp的大规模移动互联网移动管理方案
可扩展的移动支持是大规模移动互联网中的一项重要任务。基于分布式哈希表(DHT)的移动支持方案具有高度的用户可扩展性和负载均衡性,已经进行了大量的研究。然而,这些方案在查询更新性能和网络可扩展性方面存在不足。这是因为虽然叠加路由本身是有效的,但逻辑拓扑与物理拓扑之间存在不一致性,所以实际的物理网络性能不一定是有效的。本文在对马尔可夫决策过程(MDP)的叠加映射查询建模的同时,定义了结合物理层信息和应用层信息的奖励函数。在此基础上,提出了一种马尔可夫决策路由(MDR)算法,该算法改进了逆向归纳法得到全局最优策略,并能平衡时间和空间的复杂性。我们提出了一种基于DHT和mdr的移动性管理(DMDRMM)方案。数值计算结果表明,该方案继承了基于dht的管理结构的优点,优化了dDHT的更新和查询性能,尤其适用于大规模网络。
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