Neural Network based Mobility aware Prefetch Caching and Replacement Strategies in Mobile Environment
International Journal of Advanced Computer Science and Applications(IJACSA), (2013)Abstract
The Location Based Services (LBS) have ushered
the way mobile applications access and manage Mobile Database
System (MDS). Caching frequently accessed data into the mobile
database environment, is an effective technique to improve
the MDS performance. The cache size limitation enforces an
optimized cache replacement algorithm to find a suitable subset of
items for eviction from the cache. In wireless environment mobile
clients move freely from one location to another and their access
pattern exhibits temporal-spatial locality. To ensure efficient cache
utilization, it is important to consider the movement direction,
current and future location, cache invalidation and optimized
prefetching for mobile clients when performing cache replacement.
This paper proposes a Neural Network based Mobility
aware Prefetch Caching and Replacement policy (NNMPCR)
in Mobile Environment to manage LBS data. The NNMPCR
policy employs a neural network prediction system that is able to
capture some of the spatial patterns exhibited by users moving in
a wireless environment. It is used to predict the future behavior
of the mobile client. A cache-miss-initiated prefetch is used to
reduce future misses and valid scope invalidation technique for
cache invalidation. This makes the policy adaptive to clients
movement behavior and optimizes the performance compared
to earlier policies.