PINE-guided cache replacement policy for location-dependent data in mobile environment

2008 ◽  
Author(s):  
Mary Magdalene Janef ◽  
R. Parameswaran ◽  
R Nadarajan ◽  
Maytham Safar
Keyword(s):  
Replacement Policy ◽  
Dependent Data ◽  
Cache Replacement ◽  
Mobile Environment ◽  
Cache Replacement Policy

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

2010 ◽  
Vol 6 (3) ◽  
pp. 31-48 ◽  
Author(s):  
Mary Magdalene Jane.F ◽  
R. Nadarajan ◽  
Maytham Safar
Keyword(s):  
Data Access ◽  
Data Availability ◽  
Replacement Policy ◽  
Dependent Data ◽  
Access Time ◽  
Cache Replacement ◽  
Cache Replacement Policy ◽  
Active Sets ◽  
Mobile Clients ◽  
Spatio Temporal

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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