A Spatio-Temporal Cache Replacement Policy for Location Dependent Data in Mobile Environments

A Spatio-Temporal Cache Replacement Policy for Location Dependent Data in Mobile Environments

Mary Magdalene Jane.F (P.S.G. College of Technology, India), R. Nadarajan (P.S.G. College of Technology, India) and Maytham Safar (Kuwait University, Kuwait)
DOI: 10.4018/jbdcn.2010070102
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Abstract

Data caching in mobile clients is an important technique to enhance data availability and improve data access time. Due to cache size limitations, cache replacement policies are used to find a suitable subset of items for eviction from the cache. In this paper, the authors study the issues of cache replacement for location-dependent data under a geometric location model and propose a new cache replacement policy RAAR (Re-entry probability, Area of valid scope, Age, Rate of Access) by taking into account the spatial and temporal parameters. Mobile queries experience a popularity drift where the item loses its popularity after the user exhausts the corresponding service, thus calling for a scenario in which once popular documents quickly become cold (small active sets). The experimental evaluations using synthetic datasets for regular and small active sets show that this replacement policy is effective in improving the system performance in terms of the cache hit ratio of mobile clients.
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Location - Dependent Cache Replacement Policies

Several location-aware cache replacement policies have been proposed for LDIS over the past few years and the most predominant ones are explained in this section. In summary, the existing cache replacement polices can be classified into three groups.

Temporal-based cache replacement strategies, such as LRU (least recently used) has been studied by Balamash and Krunz (2004) with respect to web caching, LFU (least frequently used) and LRU-K by O’Neil and O’Neil (1993) have been studied widely in the past. Lam, Chan, and Yuen (2000) proposed a policy called invalid-LRU. They argue that the validity of the current values of data items depends on the temporal constraints and they may become out-dated and useless with the passage of time. The policy selects the invalid items in cache for replacement. In case all the items are valid and there is no invalid cache item, replacement is done using the original LRU principle.

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