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基于Kademlia的负载平衡云存储算法
引用本文:郑凯,朱林,陈优广.基于Kademlia的负载平衡云存储算法[J].计算机应用,2015,35(3):643-647.
作者姓名:郑凯  朱林  陈优广
作者单位:华东师范大学 信息科学技术学院, 上海 200062
基金项目:国家863计划项目(2013AA01A211)
摘    要:针对采用主从式结构的主流云存储系统可能出现的性能瓶颈和可扩展问题,基于分布式哈希表(DHT)技术的完全分布式云存储系统成为一种新的选择。解决好节点的负载平衡问题,是此类技术获得推广的关键。研究了Kademlia算法应用于云存储系统的负载平衡性能。考虑到算法在异构环境下负载平衡性能有明显下降,改进算法在Kademlia找出的候选存储节点中根据节点的存储能力来分配负载。仿真结果表明,改进后算法的负载平衡性能有非常明显的提高,在系统模拟运行时间足够长(如1500 h以上)时,过载节点平均下降7.0%(轻载)和33.7%(重载);文件保存成功率平均提高27.2%(轻载)和35.1%(重载),而增加的通信开销可接受。

关 键 词:云存储  负载平衡  分布式文件系统  Kademlia  peersim  
收稿时间:2014-10-11
修稿时间:2014-11-06

Load balancing cloud storage algorithm based on Kademlia
ZHENG Kai , ZHU Lin , CHEN Youguang.Load balancing cloud storage algorithm based on Kademlia[J].journal of Computer Applications,2015,35(3):643-647.
Authors:ZHENG Kai  ZHU Lin  CHEN Youguang
Affiliation:School of Information Science Technology, East China Normal University, Shanghai 200062, China
Abstract:Prevailing cloud storage systems normally use master/slave structure, which may cause performance bottlenecks and scalability problems in some extreme cases. So, fully distributed cloud storage system based on Distributed Hash Table (DHT) technology is becoming a new choice. How to solve load balancing problem for nodes, is the key for this technology to be applicable. The Kademlia algorithm was used to locate storage target in cloud storage system and its load balancing performance was investigated. Considering the load balancing performance of the algorithm significantly decreased in heterogeneous environment, an improved algorithm was proposed, which considered heterogeneous nodes and their storage capacities and distributed loads according to the storage capacity of each node. The simulation results show that the proposed algorithm can effectively improve load balance performance of the system. Compared with the original algorithm, after running a long period (more than 1500 hours in simulation), the number of overloaded nodes in system dropped at an average percentage 7.0%(light load) to 33.7%(heavy load), file saving success rate increased at an average percentage 27.2%(light load) to 35.1%(heavy load), and also its communication overhead is acceptable.
Keywords:cloud storage  load balancing  distributed file system  Kademlia  peersim
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