NOVEL APPROACH FOR BEST SIGNAL PROCESSING AND NETWORK STRUCTURE TO IMPROVE CLOUD ERP RELIABILITY AND HIGH SPEED

If the companies face difficulties in using ERP systems because of its complicated integrating and customising functions, the company can consider some other software for processing their data. On the other hand, those who are using ERP system should make precise settings for providing accurate data and timely service. An error-free network structure must be maintained by cloud ERP systems for providing enhanced service. Based on the network structure and best optimization methods, it must focus on nodes, clusters, LANs, and WANs. The novel data pre-processing consists of three core areas, and they are Pattern Recognition, Data Clustering, and Signal Processing. In this paper, Dynamic cluster formation and pattern recognition are given special weightage. For offering high-speed data transactions with data shrinking, Hybrid dynamic clustering algorithm is explained. As there is a shortage of electricity, the priority is given to energy savings by WSN (Wireless Sensor Network). The consumption of energy has decreased by permitting few cluster heads in the network, also known as nodes for communicating with the base station. A simple, effective, and computationally efficient optimization approach known as Particle swarm optimization (PSO) is utilized. With the usage of fitness function every particle poss the fitness value and even their speed it controlled using velocity. These values have been utilized by WSN for rectifying the issues like optimal deployment, clustering, node selection, and data aggregation. Efforts have been made to reduce the energy consumption occurs by the nodes and for extending the life of the network by proposing a PSO-based technique which selects the best nodes as cluster heads and a reselect mechanism for extending the network lifetime.