Cooperative Caching Strategy in Mobile Ad Hoc Networks for Cache the Replaced Data Item

Abstract

In this paper, we present a scheme, called Zone-based Cooperative Caching (ZCC) for data caching in mobile ad hoc networks. In ZCC scheme, r-hop neighbors of a mobile clients form a cooperative cache zone. The objective is to improve data availability and access efficiency by collaborating local resources of mobile clients. ZCC addresses two basic problem of cooperative caching: cache resolution and cache management. In ZCC scheme, for a local cache miss, requested client looks for data item within its zone. If no client inside the zone has cached the requested data item, zone-based cache resolution process is invoked to find the cached client before reaching the server. In this scheme, for cache management, we proposed an optimistic placement for store the replace data item in requested zone. For optimistic placement, caching status and mobile client energy level status is exchanged and maintain periodically in a zone. Simulation with ns-2.32 software were used to study the performance of the system in terms of success ratio, miss ratio, average number of messages per request, and average travel distance in hops and to compare with the performance of No Cache, SimpleCache, Hop-by-Hop Cache resolution schemes. The results demonstrate the effectiveness of the proposed scheme in terms of achieved data availability and low delay for data retrieval.

An intelligent database proactive cache replacement policy for mobile communication system based on genetic programming

“…The access probability of the data item pi depends on the earlier access rate of a data item at the client node . Data items will be removed from the cache if the measure of its access probability is lower.…”

Proactive cache replacement technique for mobile networks based on genetic programming

“…where the access probability of data item ( pi) [21,24,25] depends on the earlier access rate of a data item at the client node. Data items will be removed from the cache if the measure of its access probability is lower.…”

“…The most difficult part in GP is to determine the fitness function, different environments may have different fitness functions, and so in this research the system selects a fitness function that incorporates the most effective variables that affect cache replacement policy in the mobile environment that takes into consideration the impact of invalidation policy for enhancing data availability in the mobile environment. Therefore, on the basis of the variables that have been mentioned in Table 1, the system uses the following expression as a fitness function:where the access probability of data item () [21, 24, 25] depends on the earlier access rate of a data item at the client node. Data items will be removed from the cache if the measure of its access probability is lower.…”