Optimized Scheduling and Clustering Technique For Receiver Initiated Mac Protocol In Adhoc Wireless Sensor Network

Abstract

The Wireless Sensor Network (WSN) is a revolutionizing technology where it deploys sensor nodes to transmit data to the base station. Here, the network energy is a critical parameter metric as the sensor nodes are low power battery-operated devices and therefore it is necessary to forward the data to the sink node without any delay. Mainly the delay in contention-based Receiver-initiated MAC (RI-MAC) protocols is caused by idle listening which makes the data packet to stagnant in the nodes for longer duration. Furthermore, collision and re-transmission of data packets introduces more delay in the network. As the contention-based protocols are not sink aware, it creates data looping inside the sensor network. To overcome this, the proposed research work introduces an Enhanced Scheduling MAC (ES-MAC) protocol incorporated with Multifactor optimized Clustering with Improved Scheduling (MoC-IS) and Intra and Inter Cluster Modelling with Scheduling (IICM-S) is proposed to enhance the performance of the sensor node with effective intra node and inter node communication along improved scheduling mechanism. Here, a sink aware beacon scheduling algorithm is built over the RI-MAC that guarantees a delay-efficient communication that contributes for the enhancement of the network lifetime. Also, numerous protocols were developed for achieving the node management, yet it affected the network performance. An effective node management requires various factors such as formation of Cluster Head (CH), data flow, etc. Therefore, the proposed work incorporate MoC-IS to improve the effectiveness of intra node communication. The clustering was successively carried out the MoC algorithm and dual LEACH which considers parameters such as threshold level, battery life, and network stability. The data flow in between the CHs is calculated using hop count. Futher more, IICM-S incorporates both intra and inter cluster scheduling which operated on the parameters such as node energy, node density, node load, position of the node and link stab