Big Data Gathering Concept using RSM Algorithm to Avoid Data Traffic and Battery time Conservation

Author(s):  Abirami.S, Shivasankari.S, Brindha.S

Abstract:   The era of big data has begun, and an enormous amount of real-time data is used for the risk analysis of various industrial applications. Wireless sensor networks (WSN) technology can overcome this limitation by collecting the big data generated from source nodes and transmitting them to the data center in real time. In this study, typical residence, office, and manufacturing environments were chosen. The signal transmission characteristics of WSN were obtained by analyzing the test data. According to these characteristics, a real-time big data gathering (RTBDG) algorithm is proposed along with RSM algorithm for the risk analysis of industrial operations. In this algorithm, sensor nodes can screen the data collected from the environment and equipment according to the requirements of risk analysis. Clustering data transmission structure is then established on the basis of the received signal strength indicator (RSSI) and residual energy information. Experimental results show that RTBDG and RSM not only efficiently uses the limited energy of network nodes but also balances the energy consumption of all nodes. In the near future, the algorithm will be widely applied to risk analysis in different industrial operations.