Improving Data Access Efficiency in Social Wireless Network with Cooperative Caching

Caching is a key technique for improving the data retrieval performance of mobile clients in mobile environments. The emergence of robust and reliable technologies now brings to reality what we call "cooperative caching‖ in which mobile clients can access data items from the cache in their neighbouring peers. We discuss cooperative caching in mobile environments and propose a cooperative caching scheme for mobile systems. With our model, we extend beyond these populations to project cooperative caching behaviour in regions with millions of clients. Overall, we demonstrate that cooperative caching has performance benefits only within limited population bounds. Then optimal cooperative caching policy for minimizing electronic content provisioning cost in Social Wireless Networks (SWNETs). To reduce user-perceived latency in retrieving documents on the World Wide Web, a commonly used technique is caching both at the client's browser and more gainfully (due to sharing) at a proxy. The effectiveness of Web caching hinges on the replacement policy that determines the relative value of caching different objects. An important component of such policy is to predict next-request times. Using various Web server logs, we compared existing cache replacement policies with our server-assisted schemes. The first issue is whether Web requests from a fixed user community are distributed. It relates to a number of studies on the characteristics of Web proxy traces, which have shown that the hit-ratios and temporal locality of the traces exhibit certain asymptotic properties that are uniform across the different sets of the traces. We find that the model yields asymptotic behavior that are consistent with the experimental observations, suggesting that the various observed properties of hit-ratios and temporal locality are indeed inherent to Web accesses observed. Finally, we revisit Web cache replacement and show that the algorithm that is suggested by this simple model performs best on real trace data.