An optimal network coding based backpressure routing approach for massive IoT network

In order to mitigate the power consumption issue for the sensor's nodes, an efficient power optimized routing protocol is needed. Therefore, this paper proposes a network coding backpressure routing (NCBPR) routing scheme for a large-scale Internet of Things (IoT) networks, which exploits the backpressure algorithm in order to divert packets flow. In the network, the packets are flowing from the highly congested node to low congested node, which helps to balance the load and optimized the fair use of the battery power of all the participating nodes. It divides the network into the small clusters, where the selection of clusters head depends upon an additional parameter of battery power apart from other optimum path parameters. It also employs an efficient data aggregation mechanism, which improves the throughput of the network by eliminating redundant packets. The network has been designed by considering 300 nodes in a network and the results have been drawn in terms of network throughput, packet delivery ratio and energy consumption. The results are presented in comparison with conventional well-known information-fusion-based role assignment (InFRA) and data routing for in-network aggregation (DRINA) routing schemes. The results prove that the proposed NCBPR scheme delivers significant improvement, such as throughput which increased by 21.38 and 12.13%, packet delivery ratio improved by 24.73 and 11.38%, and sensors node's energy consumption is decreased by 61.46 and 44.35% as compared to conventional InFRA and DRINA schemes, respectively.