M2M routing protocol for energy efficient and delay constrained in iot based on an adaptive sleep mode

Abstract

In recent years, the number of machine-to-machine (M2M) networks that do not require direct human intervention has been increasing at a rapid pace. However, the need for a wireless platform to control and monitor these M2M networks, one with both a vast coverage area and a low network deployment cost, continues to be unmet. Wireless Sensor Networks (WSNs) with energy efficiency routing protocols in M2M environments are emerging to meet the challenges of such communication through network convergence. M2M communication is considered as the core of the Internet of Things (IoT). IoT refers to a network of billions of objects that can send and receive data. Energy efficiency, delay are a critical issue in M2M and there is a shortfall in IP addresses in IoT. In this chapter, an energy efficient routing protocol for Wireless Sensor Networks (WSN) is presented, which provides a platform to control and M2M networks. Inefficient energy consumption caused by nodes being active all the time is tackled using an adaptive sleep mode solution to maintain high levels of Network Performance (N.P). Firstly, a Multilevel Clustering Multiple Sink (MLCMS) with IPv6 protocol over Low Wireless Personal Area Networks (6LoWPAN) is promoted using a sophisticated mathematical equation for electing cluster heads (CH) for each level, so as to prolong network lifetime. Secondly, enhanced N.P that prolongs the life time of the system and maximises the reduction of delay is achieved through an adaptive sleep mode scheme. The sensor field is divided into quarters with different levels of cluster heads (CHs) and two optimal location sinks. The performance of the MLCMS protocol is evaluated and compared with the multi-hop low-energy adaptive clustering hierarchy (M-LEACH) protocol. MLCMS performs 62% better than M-LEACH and 147% more effectively regarding energy efficiency. Next, 6LoWPAN for the proposed model is constructed, and its impact on the performance of MLCMS by Network Simulator (NS3) simulation is evaluated. This increases the packets received by the system by 7% more than using MLCMS without 6LoWPAN and it improves the flexibility of the proposed model. Subsequently, an adaptive sleep mode scheme, based on CH’s residual energy for the active period time, is introduced for MLCMS and a comparative analysis establishes that it extends the lifetime of the system twice as much as the evaluated MLCMS without the adaptive sleep mode algorithm. Furthermore, with the sleep mode algorithm, this reduces the delay by a half and increases the delivery by 10%.