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MCEAACO-QSRP: A Novel QoS-Secure Routing Protocol for Industrial Internet of Things

With the widespread application of the Industrial Internet of Things (IIoT), the requirements for sensing equipment to collect data and information continue to increase, and industrial wireless sensor networks (IWSNs) with industrial information perception capabilities have emerged as the times require. The data stream transmission of important value information requires the network to provide safe and reliable service quality assurance. Therefore, it is imperative to meet the requirements of end-to-end delay and reliable service between nodes and solve the problems of high energy consumption and poor security of the existing Quality-of-Service (QoS) routing protocols. To this end, considering the QoS constraints of end-to-end delay, security, and energy consumption, a multiobjective secure routing model based on trust awareness is designed. Subsequently, using the advantages of the proposed model, a novel QoS-secure routing algorithm based on multiobjective chaotic elite adaptive ant colony optimization (ACO) (i.e., MCEAACO-QSRP) is proposed. Specifically, a chaotic optimization strategy is designed to initialize the population, which increases the diversity of the population and enhances the ability of the algorithm to jump out of the local optimal. In addition, the adaptive optimization strategy is designed to dynamically adjust the algorithm trend, which effectively improves the algorithm convergence speed. The performance of the proposed algorithm is evaluated in different scale scenarios. The simulation results show that compared with other state-of-the-art QoS routing solutions, the proposed MCEAACO-QSRP has obvious advantages, which can effectively improve routing security, reduce network energy consumption, and satisfy multi-QoS constrains for the end-to-end delay and reliable service.