An Improved Ggp Based Cluster Head Routing for Recovering and Sensing Data Aggregation Integrity in Wireless Sensor Networks

In earlier works several data aggregation schemas based methods have been proposed to overcome the problems of the privacy in wireless sensor networks. These methods provides efficient result to analysis of secure data with traditional aggregation because cluster heads can straightforwardly comprehensive the cipher texts not including decryption; accordingly, reduces the transmission overhead in wireless sensor networks. But still the data aggregation schema occurs two major problems in aggregation process; the major cluster head does not receive the entire data and cannot authenticate data truthfulness and dependability via between message digest. To conquer these problems in this work first proposed a Generalized Geometric programming method to select best cluster head or aggregation of the data by finding the shortest hop inter-CH routing. For this scheme, transmission overhead reduced and improve the coverage-time maximization is created as a signomial optimization difficulty with the purpose of is capably solved using Generalized Geometric Programming (GGP) techniques. The optimal cluster sizes of the individual data aggregation are achieved beginning this examination. Experimentation results show that the transmission overhead is still concentrated even if our approach is recoverable on common sensing data. Furthermore, the design has been widespread and adopt on together homogeneous and heterogeneous wireless sensor networks data aggregation schemas while using GGP clustering (or) cluster head routing selection. Keywords— Wireless Sensor Networks; Data Aggregation Using Pattern Codes; Pattern Comparison by Cluster-Head RCDA; Routing; Generalized Geometric Programming (GGP)