Achieving Flexible Cache Consistency for Pervasive Internet Access

Yu Huang, Jiannong Cao, Zhijun Wang, Beihong Jin, Yulin Feng
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引用次数: 49

Abstract

Caching is an important technique to support pervasive Internet access. Cache consistency measures the deviation between the cached data and the source data. In mobile computing environments, especially with ad hoc networks, users are in great need of the flexibility in tuning their consistency requirements, in order to make tradeoffs between the specified cache consistency and the cost incurred. Existing works have used delta consistency (DC) and probabilistic consistency (PC) which, to some extent, provide the users with such flexibility. In this paper, we propose a general consistency model called probabilistic delta consistency (PDC). PDC covers all existing consistency models including DC and PC, and integrates the flexibility granted by both DC and PC. Thus, PDC enables the users to flexibly specify their consistency requirements in two orthogonal dimensions, namely the deviation in time/value and the ratio of queries gaining the specified consistency. We also propose a consistency maintenance algorithm, called flexible combination of push and pull (FCPP), which can meet users' consistency requirements specified under the PDC model. An analytical model is derived to achieve the optimized combination of push and pull, so as to ensure the user-specified consistency requirements, while minimizing the consistency maintenance overhead. Extensive simulations are conducted to evaluate the performance of the FCPP algorithm. Evaluation results show that, compared with the widely used dynamic TTR algorithm, FCPP can save up to 68% of the traffic overhead and reduce the query delay by up to 84%
为普及互联网接入实现灵活的缓存一致性
缓存是支持普遍Internet访问的一项重要技术。Cache一致性是指缓存数据与源数据之间的偏差。在移动计算环境中,特别是在ad hoc网络中,用户非常需要灵活地调优其一致性需求,以便在指定的缓存一致性和所产生的成本之间进行权衡。现有的工作已经使用了增量一致性(DC)和概率一致性(PC),它们在一定程度上为用户提供了这样的灵活性。本文提出了一种通用的一致性模型,称为概率增量一致性(PDC)。PDC兼容现有的所有一致性模型,包括DC和PC,并集成了DC和PC的灵活性。因此,PDC使用户可以在两个正交的维度上灵活地指定一致性要求,即时间/值的偏差和获得指定一致性的查询的比率。提出了一种可满足PDC模型下用户一致性要求的推拉柔性组合(FCPP)一致性维护算法。推导出一种解析模型,实现推拉的优化组合,以保证用户指定的一致性要求,同时最小化一致性维护开销。通过大量的仿真来评估FCPP算法的性能。评估结果表明,与广泛使用的动态TTR算法相比,FCPP可以节省高达68%的流量开销,减少高达84%的查询延迟
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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