Stochastic Heuristic Optimization based Multi-Query Processing in Wireless Sensor Network using Genetic Algorithm

Wireless Sensor Network is an infrastructure comprising of sensing, and computing. The communication elements in sensor network give capability to instrument, watch, and respond to events and phenomenon in a particular situation. Query processing in sensor network first transfers the query generated position to the node where the result obtained is similar to this query. Collaborative Query-Centric Framework (COSE) heterogeneous sensor networks are effectual and well-organized for processing of queries. Query processing with respect to energy efficiency attain single pipeline of query processing but fails to address the issues related to multiple pipeline of query processing. COSE major drawback is that it is unable to attain an optimal solution for multiple pipelines. Next, Pocket Driven Trajectories (PDT) algorithm monitors the query processing based on spatial layout of the selected nodes. PDT algorithm efficiently adapts to different types of data collection paths but not effective for multicast query phase. To develop a multiple query processing strategy in wireless sensor network, Stochastic Heuristic Optimization using Genetic Algorithm (SHO-GA) is introduced. The SHO-GA framework process the multiple query plans based on the closeness of nodes required to answer the user query. The multi-query processing using Genetic Algorithm (GA) takes the associations with FROM clause and other multiple query operators. The SHO-GA framework carries the probability of crossover, mutation and the pre-specified number of generations as