Title :
A scalable low-latency cache invalidation strategy for mobile environments
Author_Institution :
Dept. of Comput. Sci. & Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
Caching frequently accessed data items on the client side is an effective technique for improving performance in a mobile environment. Classical cache invalidation strategies are not suitable for mobile environments due to frequent disconnections and mobility of the clients. One attractive cache invalidation technique is based on invalidation reports (IRs). However, the IR-based cache invalidation solution has two major drawbacks, which have not been addressed in previous research. First, there is a long query latency associated with this solution since a client cannot answer the query until the next IR interval. Second, when the server updates a hot data item, all clients have to query the server and get the data from the server separately, which wastes a large amount of bandwidth. In this paper, we propose an IR-based cache invalidation algorithm, which can significantly reduce the query latency and efficiently utilize the broadcast bandwidth. Detailed analytical analysis and simulation experiments are carried out to evaluate the proposed methodology. Compared to previous IR-based schemes, our scheme can significantly improve the throughput and reduce the query latency, the number of uplink request, and the broadcast bandwidth requirements.
Keywords :
cache storage; client-server systems; mobile computing; IR interval; IR-based cache invalidation algorithm; broadcast bandwidth; broadcast bandwidth requirements; cache invalidation strategies; frequently accessed data items; invalidation reports; mobile computing; mobile environment; mobile environments; power conservation; query latency; scalable low-latency cache invalidation strategy; uplink request; Analytical models; Bandwidth; Batteries; Broadcasting; Computational modeling; Delay; File systems; Handheld computers; Mobile computing; Network servers;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2003.1232276