Congestion free opportunistic multipath routing load balancing scheme for Internet of Things (IoT)

Abstract

Internet of Things (IoT) interconnects billions of devices to form a heterogeneous network over the Internet. The heterogeneous communication infrastructure of IoT opens a door for the research community to design new protocols by utilizing minimal resources of these tiny devices to achieve accurate results. Therefore, the research community suggests various techniques to resolve the load balancing issue of IoT and prolong the network lifetime. Although, these techniques are effective at some stage in managing the load balancing issue, they have some side effects on network performance such as high communication costs, end-to-end (E2E) delay, packet lost ratio (PLR), throughput, and individual sensor devices lifespan, etc. Therefore, an efficient lightweight load balancing routing protocol is needed to be developed to address the aforementioned issues in IoT networks. In this paper, Dynamic hop selection static routing protocol (DHSSRP) is proposed to resolve the load balancing issue of IoT networks in congestion-free and priority-based communication infrastructure. The proposed DHSSRP routing protocol priorities the sensitive/critical information of sensors devices with static routing and divert the neighbor’s sensor communication with an alternate hop selection path, which manages the network traffic in a congestion-free environment. The traffic management of the DHSSRP routing protocol based on priority-based information balances the energy consumption with a balanced traffic environment, which maximizes the lifespan of the deployed IoT devices in the network. The results captured during simulation for the proposed scheme were compared with the field-proven scheme, which showed a significant improvement for the metrics, such as communication cost, computational cost, traffic congestion, throughput, PLR, and network lifetime. Moreover, the results observed for an individuals sensor devices to participate in the network until the end-stage showed a 95.8 % result with the same onboard battery power.