Bloom Filter VS Weighted Bloom Filte

With the development of Internet technologies and WWW services, more and more attention is paid to the Web traffic and page access delay , which are the key issues affecting the continuous growing of Internet . Proxy Cache,an effective technique to solve these issues, is a hot research area . Some research works have been conducted on this area and result in some fruits . Research on Proxy Cache is quiet complicated because there are a lot of problems such as replacement strategy, cache consistency, cache sharing and performance analysis. Though studying of Proxy Cache has been made of years, few of these problems have been solved successfully. This thesis, concentrates on topic of cache. The contents of shared message are represented by Bloom filter. This technique greatly reduces the space needed for page indexing and decrease the access delay. A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to determine a certain element in the set . Weighted Bloom filters and counting Bloom filters have been suggested as means for sharing Web cache information . Bloom filters are transmitted among shared proxies instead of sending the full list of cache contents .In this thesis, a summary about the current research and application onBloom filter is presented, and then a mathematical comparison between the Bloom filter and weighted Bloom filter is given. It is proved that weighted Bloom filter has lower false prediction rate than Bloom filter. But the simulation results shown that Bloom filter has lower prediction rate and it is better than weighted Bloom Filter. The major reason is weighted Bloom filter needs very strong conditions, which cannot be satisfied in the real world.Finally, the problems in Bloom filter and the future research direction and measure are pointed out in this paper.