Design of Mutated Harmony Search Algorithm for Data Dissemination in Wireless Sensor Network

In the recent years, the researcher has to face new challenges due to the complexity of technological an advances in Wireless Sensor Network (WSN). Sensor based networks are a special category of a distributed network that is used to provide communication among the sensor nodes. The wireless sensor network consists of various classes of sensors like thermal, infrared, optical, and seismic for the measurement of temperature, heat, radiation, humidity which requires constant monitoring and detection in specific events. A sensor's with limited functionality both in computations, battery voltage keeps periodic sensing physical or environmental of ecological factors. Sporadic events such as detecting border intrusion, flood detection and habitat exploration of animals. The design of a WSN depends drastically on continuity and coverage of the network. Connected with that energy constrained is considered as one of the important issues to balance the network load and to extend the network life. An optimal energy efficient cluster based routing algorithm is required for effective data diffusion. Conventional protocol like LEACH, HEED, PEGASIS protocol etc., fails to balance the network load and the coverage area when the sensor nodes are deployed in large scale. In harmony search algorithm (HSA) absence of gradient search leads the parameter search is in the local region where the required optimal solution remains outside the local region. HSA is heuristic algorithm uses random search with constant harmony memory consideration rate. This paper focuses on designing a Meta-heuristic optimized routing protocol for a distributed network using mutated harmony search algorithm (MHSA) to improve the energy efficiency by simultaneously analyzing the cluster patching. Cluster patching is examined for improving network coverage and connectivity thereby to optimize the energy distribution in WSN. MHSA is a refinement of heuristic algorithm in the global search by adjusting the harmony memory consideration rate HMCR. To improve the performance and efficiency exact balancing of diversification and intensification is done by varying the Pitch adjusting rate PAR and bandwidth BW. Parametric results are compared with the standard heuristics algorithm HSA, GA, and PSO. The computational time and the experimental results show the proposed MHSA gives 85% of connectivity improved that ensures the success of cluster formation for an increased number of nodes to increase increases the network lifetime when compared with existing algorithms.