A Trust and Energy based Routing using Gorilla Troops Optimization in RPL Networks

Internet of Things (IoT) connected digital gadgets help to improve the convenience and appeal of human life by accompanying a new era of innovation. These smart objects connected to IoT employ routing protocols and are typically organized as Low-Power and Lossy Networks (LLNs). IoT devices are extremely vulnerable to a wide range of internal and external threats that could have disastrous and lethal effects. Existing trust-based methods do not adequately account for nodes' mobility or evaluate them for dynamic situations, which is an important requirement for smart applications. To overcome this problem, Trust and Energy based Multiobjective GTO - RPL (TEMGTO-RPL) is proposed, which provides trust-based secured energy-efficient solutions to the RPL networks using the Gorilla Troops Optimization (GTO) algorithm. TEMGTO-RPL considers fitness functions such as trust value, energy ratio, the distance between the nodes and Packet Delivery Rate (PDR) to select an optimal node in an IoT network. The proposed technique performs better in terms of parameters like delay, average packet delivery ratio, average energy consumption, overhead in routing, and throughput. The TEMGTO-RPL achieves a minimum delay of 0.93 sec and consumed minimum energy of 1.05 J.