An Effective Hybrid and Adaptive Caching Network Framework Approach In Time-to–Live (TTL) Based Data Item for Peripatetic Computing Environment

Abstract Caching is a well established technique to improve the efficiency of data access. This research paper introduces a Hybrid and Adaptive Caching (HAC) approach to cache the data item based on the varying size, and, Time-to-Live (TTL) based invalidation of the data item in a mobile computing environment. Mobile nodes establish single-hop communication with the base station and ad-hoc peer to peer communication with other neighbor nodes in the network to access data items. The proposed work adjusts the caching functionality level based on the size of the data item and stores the cached data item in two different storage systems. The cache of each node is separated into Temporary Buffer (TB) and Permanent Buffer (PB) to improve the data access efficiency. This approach is based on the fact that the smaller size data (e.g. stocks) are updated for shorter Time-to-Live (TTL) whereas the larger size data (e.g. video) are updated only for longer TTL. This proposed work also suggests an adaptive cache replacement and cache invalidation technique to resolve the issues regarding bandwidth utilization and data availability. In cache replacement technique, the cached data item is effectively replaced based on the size of the data item and TTL value. A timestamp-based cache invalidation strategy where the cached data is validated according to the update history of the data items has also been introduced in this paper. The threshold values have greater impact on the system performance. Therefore, the threshold values are fine tuned such that they do not affect the system performance. The proposed approaches significantly improve the query latency, cache hit ratio and efficiently utilize the broadcast bandwidth. The simulation result proves that the proposed work outperforms the existing caching techniques.