Brain Storm Water Optimisation-Driven Secure Multicast Routing and Route Maintenance in IoT

Abstract

In several Internet of Things (IoT) applications, messages are disseminated to some objects or nodes based on multicast transmissions. However, previous multicast routing schemes in IoT focussed mainly on the ad-hoc sensor network, but they are not robust and responsive in the IoT environment. Hence, this paper introduces the multicast routing protocol based on the proposed optimisation algorithm, named Brain Storm Water Optimisation (BSWO), in the IoT network. By the multicast routing protocol, the multicast path is designed from a multicast source node to various destinations. The multicast source node forwards packet to multiple destinations simultaneously. Initially, the nodes in the IoT network are simulated together and perform the multicast routing process effectively using the proposed optimisation framework. The multicast routing protocol performs the multicast routing mechanism using the multiobjective factors, such as distance, delay, energy, link-quality factor and trust. The multicast routing path is effectively chosen based on the developed BSWO through fitness measures. The proposed BSWO is designed by integrating the Brain Storm Optimisation (BSO) and Water Wave Optimisation (WWO), respectively. The path with the minimum distance is selected as an optimal path using the fitness parameters like delay, distance, trust, energy and link-quality factor. The proposed optimisation algorithm effectively performs the multicast routing mechanism by integrating the parametric features from both the optimisation algorithms. Once the multicast routing mechanism is done, the route maintenance process is carried out in the simulated IoT network to recover the link breakage. The proposed BSWO outperformed other methods with the minimal delay of 0.0682[Formula: see text]s, minimal average routing distance of 178.4[Formula: see text]m, maximal energy of 39.59[Formula: see text]J, maximal throughput of 87.75% and maximal trust of 90%, respectively.