This paper discusses the multiple node disjoint paths protocol (MNDP) for mobile ad hoc networks. A mobile ad hoc network is a collection of mobile nodes that cooperate without networking infrastructure so as to form a temporary network that meets some immediate needs. The MNDP protocol detects multiple paths and distributes transmitted packets over these paths. Such distribution reduces congestion and packet end-to-end delay, and increase the delivery ratio. The MNDP protocol detects multiple paths, assigns them a priority values based on the routes hop count and uses the shortest routes among them more frequently. The simulation results show that the proposed protocol has achieved an enhancement on packet delivery ratio, up to 16%, as compared to the Ad Hoc On-demand Distance Vector routing protocol (AODV) protocol. Finally, the results are obtained based by the GloMoSim 2.03 simulations.

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This Matching input keywords with historical or information domain is an important point in modern computations in order to find the best match information domain for specific input queries. Matching algorithms represents hot area of researches in computer science and artificial intelligence. In the area of text matching, it is more reliable to study semantics of the pattern and query in terms of semantic matching. This paper improves the semantic matching results between input queries and information ontology domain. The contributed algorithm is a hybrid technique that is based on matching extracted instances from booth, the queries and in information domain. The instances extraction algorithm that is presented in this paper are contributed which is based on mathematical and statistical analysis of objects with respect to each other and also with respect to marked objects. The instances that are instances from the queries and information domain are subjected to semantic matching to find the best match, match percentage, and to improve the decision making process. An application case was studied in this paper which is related to renewable energy, where the input queries represents the customer requirements input and the knowledge domain is renewable energy vendors profiles. The comparison was made with most known recent matching researches.

Wireless sensor networks (WSNs)

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