移动环境中基于组的移动客户端协同缓存管理

Chi-Yin Chow, H. Leong, A. Chan
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引用次数: 57

摘要

缓存是提高移动客户端数据检索性能的关键技术。稳健可靠的点对点(P2P)通信技术的出现使我们所说的“协作缓存”成为现实,其中移动客户端不仅可以从移动支持站检索数据项,还可以从相邻对等点的缓存中访问数据项,从而为移动数据缓存引入了一个新的维度。这项工作在基于拉的移动环境中扩展了一种称为COCA的协作缓存方案。在COCA框架的基础上,我们提出了一种基于组的协作缓存方案,称为GroCoca,其中我们将紧耦合组(TCG)定义为具有相似移动模式和具有相似数据亲和力的一组对等体。GroCoca采用集中式增量聚类算法动态发现所有TCG,同一TCG中的mh协同管理各自的缓存数据项。在仿真实验中,GroCoca可以有效地降低访问延迟和服务器请求率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Group-based cooperative cache management for mobile clients in a mobile environment
Caching is a key technique for improving data retrieval performance of mobile clients. The emergence of robust and reliable peer-to-peer (P2P) communication technologies now brings to reality what we call "cooperating caching" in which mobile clients not only can retrieve data items from mobile support stations, but also can access them from the cache in their neighboring peers, thereby inducing a new dimension for mobile data caching. This work extends a cooperative caching scheme, called COCA, in a pull-based mobile environment. Built upon the COCA framework, we propose a group-based cooperative caching scheme, called GroCoca, in which we define a tightly-coupled group (TCG) as a set of peers that possess similar movement pattern and exhibit similar data affinity. In GroCoca, a centralized incremental clustering algorithm is used to discover all TCGs dynamically, and the MHs in same TCG manage their cached data items cooperatively. In the simulated experiments, GroCoca is shown to reduce the access latency and server request ratio effectively.
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