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In this paper, we propose a new web search engine model based on index-query bit-level compression. The model incorporates two bit-level compression layers both implemented at the backend processor (server) side, one layer resides after the indexer acting as a second compression layer to generate a double compressed index, and the second layer be located after the query parser for query compression to enable bit-level compressed index-query search. This contributes to reducing the size of the index file as well as reducing disk I/O overheads, and consequently yielding higher retrieval rate and performance. The data compression scheme used in this model is the adaptive character wordlength (ACW(n,s)) scheme, which is an asymmetric, lossless, bit-level scheme that permits compressed index-query search. Results investigating the performance of the ACW(n,s) scheme is presented and discussed.

ABSTRACT

The location-aided routing scheme 1 (LAR-1) and probabilistic algorithms are combined together into a new algorithm for route discovery in mobile ad hoc networks (MANETs) called LAR-1P. Simulation results demonstrated that the LAR-1P algorithm reduces the number of retransmissions as compared to LAR-1 without sacrificing network reachability. Furthermore, on a sub-network (zone) scale, the algorithm provides an excellent performance in high-density zones, while in low-density zones; it preserves the performance of LAR-1. This paper provides a detailed analysis of the performance of the LAR-1P algorithm through various simulations, where the actual numerical values for the number of retransmissions and reachability in high- and low-density zones were computed to demonstrate the effectiveness and significance of the algorithm and how it provides better performance than LAR-1 in high-density zones. In addition, the effect of the total number of nodes on the average network performance is also investigated.