An Efficient and Optimized Service Discovery Methodology for QoS Aware Service Oriented Business Intelligence
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The current and future business processes would be service oriented. The required service is selected using discovery process. The discovery process uses in-memory parse tree construction or callback based document parsing. Existing service discovery systems stores both functional attributed and QoS attributed in tree data structures and they are time consuming, space consuming, requires frequent parse tree construction in various location, difficult to replicate and distribute parse tree and replicated parse trees are inconsistent. This paper proposes an efficient methodology to improve the performance of in memory parse tree discovery process over extended web service architecture. The system uses two parallel discovery algorithms, Synchronous and Asynchronous algorithms for service discovery, both algorithms uses the tree and indexed data structure for service discovery and the later also uses a bitmap table to verify functional requirements. The services are selected and ranked based on user request using Coefficient of Variance. The proposed algorithms are detailed in this paper. The experimental results are conducted on benchmark dataset are discussed. The proposed system ensures availability, consistency, effective space utilization, eases replication and distribution and improves response time for service discovery by 30%.
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