MBSR: MIMO Based Sink Relocation for Path Selection in IoT Based WSN

Abstract

Wireless Sensor Networks have extended its functionalities by integrating with the Internet of Things and are highly proficient when it is incorporated with other technologies. This demands communication with lesser energy consumption and one such idea of low energy consumption is low energy path selection by a mobile sink node. Path selection requires a good Signal Interference Noise Ratio (SINR) which is calculated for the positioned mobile sink. Thus, a high-quality transmission path is selected by choosing a path to obtain better SINR. MBSR algorithm considers hierarchical clustering schemes and heads are elected to monitor the network. Heads of the clusters communicate to IoT applications using Multiple Input and Multiple Output Dual Antennas. The proposed MBSR scheme utilizes a path optimization technique and finds a suitable path to establish links to end user and real-time environments. The proposed MBSR mechanism employs three phases of execution. Phase 1: Cluster Creation, Phase 2: SINR Analysis for Path Selection. Phase 3: Data transmission to MIMO Devices and in turn forwards to static sinks that connect to end-user using the internet. MBSR improves transmission quality and the proposed scheme is tested for various network parameters to check transmission quality and is compared with existing methodologies.

Keywords: Hierarchical Clustering, IoT, MIMO, Signal Interference Noise Ratio, Wireless Sensor Network