In this paper, we study the problem of efficient processing of conjunctive queries in Peer-to-Peer systems based on Distributed Hash Tables (P2P DHT, for short). The basic idea of our approach is to cache the search result for the queries submitted in the past, and to use them to improve the performance of succeeding query processing. More concretely, we propose to adopt Bloom filters as a concrete implementation of such a result cache rather than a list of items used in many conventional schemes. By taking such an approach, the cache size for each conjunctive query becomes as small as the size of each file index. The performance of the proposed scheme is evaluated by simulation. The result of simulation indicates that the proposed scheme is particularly effective when the size of available memory in each peer is bounded by a small value, and when the number of peers is 100, it reduces the amount of data transmissions of previous schemes by 75%.

P2P DHT (Peer-to-Peer Distributed Hash Table) is one of typical techniques for realizing an efficient management of shared resources distributed over a network and a keyword search over such networks in a fully distributed manner. In this paper, we propose a new method for supporting conjunctive queries in P2P DHT. The basic idea of the proposed technique is to share a global information on past trials by conducting a local caching of search results for conjunctive queries and by registering the fact to the global DHT. Such a result caching is expected to significantly reduce the amount of transmitted data compared with conventional schemes. The effect of the proposed method is experimentally evaluated by simulation. The result of experiments indicates that by using the proposed method, the amount of returned data is reduced by 60% compared with conventional P2P DHT which does not support conjunctive queries.