The development of wireless sensor network results in faster technological development and its fundamental problem of network life time in the given energy constraints leads to several research study and its optimization. Sensor networks revolutionize the paradigm of collecting and processing information from diverse environments. In this paper proposed the distributed clustering optimization to determine the better network performance using the meta-heuristic approach based on Improved Harmony Search Algorithm (IHSA) principle. HAS is a music-based meta-heuristic optimization method, implemented in real time to minimize the intra-cluster distances between the cluster members and cluster heads (CHs) to optimize the energy distribution of the WSNs. Further Ant Entropy based Data Aggregation (AEDA) algorithm is applied to maximum possible energy saving through data aggregation under different data traffic. The simulation carried out using MATLAB to study the performance matrix in the heterogeneous network nodes. The proposed protocol realization compared with Metaheuristic Algorithms using different empirical test values. The protocol evaluation studies provides a balance between error reduction and maximize the network lifetime improvement. Keywords—Ant Entropy based Data Aggregation, Clustering Distributed clustering, Harmony Search Algorithm, Wireless sensor network.
