Improve Performances of Wireless Sensor Networks for Data Transfer Based on Fuzzy Clustering and Huffman Compression

In today’s world, the main challenge is to save use energy optimally. The IoT devices generate a large amount of data for wide applications. Considering application perspective in market, one instance technology, that wireless sensor network, factors like energy, storage capacity, computation power, and limitations communication bandwidth resources are reason using fusion. Data fusion aggregation networks (WSNs) such minimum consumed an essential issue. most clustering models, carried out by cluster-head (CH). proposed algorithm, lossless cascode Huffman compression algorithm. Due correlation among nodes, sensed each node compared with node; after removing redundancy, coded transmitted node. CH selected algorithm based on fuzzy logic according residual distance from sink Various type-I systems Mamdani Takagi-Sugeno type-II used. this paper, selection algorithms evaluated three scenarios terms number live received packets CHs, proper distribution rate, other parameters LEACH protocol, network lifetime, energy. following, demonstrate performance new simulations performed MATLAB method. results show environments high improves rate 8% conventional compression, while low correlation, these two perform almost same. This helps reduce consumption network.