CBPR: A Cluster-Based Backpressure Routing for the Internet of Things

The concept of the Internet of Things (IoT)-based Wireless Sensor Network (WSN) is rapidly gaining wide-spread recognition and acceptance in our day-to-day lives. Nowadays, the application of the IoT sensor nodes in various domains of endeavors such as health-care, smart homes, industrial and production sectors, control networks, and in many other fields has continued to increase steadily. In IoT-based WSN, sensor nodes dynamically join the internet and collaborate to accomplish a mission by sensing and collecting event data from the application field. The sensor nodes thus forward the collected information to the sink nodes or to the nearest base station for further transmission. However, one of the significant drawbacks of the IoT-based WSN networks is that the battery life of the sensor nodes is often short-lived due to the energy-limited nature of the electronic sensors, resulting in the network’s short lifetime. Thus, prolonging the lifetime duration of the sensor nodes becomes a fundamental task. Whether the battery life of a sensor node is extended for a reasonable length of time or depleted in a moment depends mainly on the energy efficiency of the underlying routing protocol. Therefore, the issue of network lifetime can be fundamentally addressed by implementing an efficient and robust energy-aware routing protocol for sustainable and prolonged network operation time in a WSN based IoT network scenario. In this paper, a cluster-based Backpressure routing (CBPR) scheme has been proposed, which targets to prolong the network lifetime and enhance the data transmission reliability using energy load-balancing mechanism. For every cluster of the sensor node, the CBPR scheme elects a cluster head which has the highest energy level and the shortest distance to the sink node. The proposed CBPR routing scheme further utilizes a very robust data aggregation algorithm to checkmate and prevent the circulation of redundant data packets in the network while also exploiting the Backpressure scheduling machine for data packets queueing and for route selection, which allows it to select the next-hop sensor node based on the queue length value of the sensor nodes. Extensive simulations have been performed to evaluate the efficiency of the proposed CBPR routing scheme, which was compared with that of other well-known routing schemes such as the Information Fusion Based Role Assignment and Data Routing for In-Network Aggregation in terms of throughput, energy consumption, and packet delivery ratio.