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Top1. Introduction
The network paradigm that bridges the gap between the physical and cyber world is the IoT. A variety of objects/ things, like sensors, RFID tags, mobile devices, and actuators, comprises the network. The wireless and wired networks are used for liking the objects to the network. Numerous services and applications are promoted as the IoT is progressed in the new digital context (Tang et al., 2014). The network protocols and infrastructure provided efficient and effective communication for implementing the IoT successfully. Hence, the service performance of IoT has a major impact on the performance of the network (Huang et al., 2014). One of the active regions of research in the IoT is data communication. In the earlier times, the IoT devices communicate among themselves through the wireless channel even though they had limited battery and computing capacity. The IoT is used mostly in object activating and data sensing environments (Zhang et al., 2016). In IoT data communication, the major concern is maintaining the Quality of Service (QoS) level and minimizing the network resource. More diverse applications follow the rapid evolution of IoT that includes combiningIoT with big data and cloud computing services (Alletto et al., 2016). The satisfaction of the QoS constraints remains a challenge in the rapid growth of IoT-based sensor nodes. The QoS constraints should be guaranteed in dynamic scenarios (Huang et al., 2016).
The paths in the network nodes are constructed and sustained through Routing Protocol (RP). Hence, the RPbehavior depends strongly on the performance of the network. Only a few protocols are designed for fulfilling the IoT requirements; among them, some of the protocols are Light-weight Ad-hoc distance-based protocol (Clausen et al., 2017) and IPv6 RP for LowPower and Lossy Networks (RPL) (Alexander et al., 2012). A less complex and more light-weight solution is offered byLightweight Ad-hoc distance-based protocol, whereas the standard RP is provided by the RPL (Iovaet al., 2016). A multicast data traffic is generated by the IoT applications like Industrial IoT (Boyeset al., 2018) for sending the messages to the node groups. For instance, the multicast message is sent to the specific node groups through the central manager device to reach the desired temperature and adjust the operation. In addition, the machines are started and stopped simultaneously by the central device through single transmission. In the Industrial LLNs, the functional requirement of the RP is confirmed usingthe Internet Engineering Task Force (IETF) for supporting the Request for Comments (RFC) document. However, the routing approach used in the IoT networks failed to provide feasible support for the traffic pattern. Although the RPL sends multicast messages, it had complex implementation and required high memory usage(Sobralet al., 2019).
The main purpose of the research is the progression of the Iterative model for energy-aware multicast routing for IoT. The developed iterative CrowWhale-Energy Trust Routing (iterative CrowWhale-ETR) is developed by considering the parameter, such as trust value of node and energy consumption. Initially, the effective nodes for the multicast routing are selected by measuring the nodes' QoS, trust, and energy level. Then, the fitness factor selects the secure nodes for routing based on the fitness of specific nodes in the network. After selecting the secure nodes, the route for transmission is discovered and selected using the Iterative crowwhale optimization. The Iterative crowwhale optimization is modeledby including the historical terms from the Taylor series in the CrowWhale algorithm. Finally, route maintenance is done relies on the evaluation metric of nodes in the network.
The main objectives of the research are: