摘要
为了保证网络存储的负载平衡并避免在节点或磁盘故障的情况下造成不可恢复的损失,提出一种基于均衡数据放置策略的分布式网络存储编码缓存方案,针对大型高速缓存和小型缓存分别给出了不同的解决办法。首先,将Maddah方案扩展到多服务器系统,结合均衡数据放置策略,将每个文件作为一个单元存储在数据服务器中,从而解决大型高速缓存问题。然后,将干扰消除方案扩展到多服务器系统,利用干扰消除方案降低缓存的峰值速率,结合均衡数据放置策略,提出缓存分段的线性组合,从而解决小型缓存问题。最后,通过基于Linux的NS2仿真软件,分别在一个和两个奇偶校验服务器系统中进行仿真实验。仿真结果表明,提出的方案可以有效地降低峰值传输速率,相比其他两种较新的缓存方案,提出的方案获得了更好的性能。此外,采用分布式存储虽然限制了将来自不同服务器的内容组合成单个消息的能力,导致编码缓存方案性能损失,但可以充分利用分布式存储系统中存在的固有冗余,从而提高存储系统的性能。
In order to ensure the load balance of network storage and to avoid unrecoverable loss in case of node or disk fai-lures,this paper proposed a distributed storage and coding scheme based on balanced data placement strategy,which gave different solutions for large caches and small caches.Firstly,it extended the Maddah scheme to multi-server system,and stored each file as a unit in the data server by combining balanced data placement strategy to solve the large-scale cache problem.Then,it extended the interference cancellation scheme to the multi-server system.It used the interference cancellation scheme to reduce the peak rate of the cache,and proposed the linear combination of cache segments by combining balanced data placement strategy so as to solving the problem of small caching.Finally,it carried out simulation experiments in one and two parity check server systems respectively through Linux-based NS2 simulation software.The simulation results show that the proposed scheme can effectively reduce the peak transmission rate.It achieves better performance comparing with the other two new ca-ching schemes.In addition,although distributed storage limits the ability to combine content from different servers into a single message,resulting in performance loss of coding and caching schemes,it can make full use of the inherent redundancy in distributed storage systems,thereby improving the performance of storage systems.
作者
陈雪
胡玉平
Chen Xue;Hu Yuping(Dept.of Computer Science&Engineering,Guangzhou College of Technology&Business,Guangzhou 510850,China;School of Information Science,Guangdong University of Finance&Economics,Guangzhou 510320,China)
出处
《计算机应用研究》
CSCD
北大核心
2020年第4期1194-1199,共6页
Application Research of Computers
基金
广东省自然科学基金资助项目(2016A030313717)。