The IEEE 802.15.4 standard is one of the widely adopted networking specification for Internet of Things (IoT). It defines several physical layer (PHY) options and medium access control (MAC) sub-layer protocols for interconnection of constrained wireless devices. These devices are usually battery-powered and need to support requirements like low-power consumption and low-data rates. The standard has been revised twice to incorporate new PHY layers and improvements learned from implementations. Research in this direction has been primarily centered around improving the energy consumption of devices. Recently, to meet specific Quality-of-Service (QoS) requirements of different industrial applications, the IEEE 802.15.4e amendment was released that focuses on improving reliability, robustness and latency. In this paper, we carry out a performance-to-cost analysis of Deterministic and Synchronous Multi-channel Extension (DSME) and Time-slotted Channel Hopping (TSCH) MAC modes of IEEE 802.15.4e with 802.15.4 MAC protocol to analyze the trade-off of choosing a particular MAC mode over others. The parameters considered for performance are throughput and latency, and the cost is quantified in terms of energy. A Markov model has been developed for TSCH MAC mode to compare its energy costs with 802.15.4 MAC. Finally, we present the applicability of different MAC modes to different application scenarios.

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A Performance-to-Cost Analysis of IEEE 802.15.4 MAC With 802.15.4e MAC Modes

Wireless Sensor Networks (WSNs) are a type of self-organizing networks with limited energy supply and communication ability. One of the most crucial issues in WSNs is to use an energy-efficient routing protocol to prolong the network lifetime. We therefore propose the novel Energy-Efficient Load Balancing Ant-based Routing Algorithm (EBAR) for WSNs. EBAR adopts a pseudo-random route discovery algorithm and an improved pheromone trail update scheme to balance the energy consumption of the sensor nodes. It uses an efficient heuristic update algorithm based on a greedy expected energy cost metric to optimize the route establishment. Finally, in order to reduce the energy consumption caused by the control overhead, EBAR utilizes an energy-based opportunistic broadcast scheme. We simulate WSNs in different application scenarios to evaluate EBAR with respect to performance metrics such as energy consumption, energy efficiency, and predicted network lifetime. The results of this comprehensive study show that EBAR provides a significant improvement in comparison to the state-of-the-art approaches EEABR, SensorAnt, and IACO.

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Energy-Efficient Load Balancing Ant Based Routing Algorithm for Wireless Sensor Networks

IoT objects that have a resource constrained nature resulting in a number of attacks in the routing protocol for lossy networks and low-power networks. RPL is very vulnerable to selfish behaviours and internal attacks though they are built with encryption protection to secure messages. To address this vulnerability, in this paper, we propose a novel trustworthiness methodology based on metric for incorporating trust evaluation, enhancing the robustness of security mechanism. Simulation results indicate that the proposed work is efficient in terms of throughput, nodes’ rank changes, energy consumption and packet delivery ratio. Moreover, using mathematical modelling, it has been observed that this methodology meets the demands of loop-freeness, optimality and consistency. This shows that this metic has both monotonicity and isotonicity requirements to enable the routing protocol. Incorporating the concepts of game theory, we can use this technique as a strategy to iterate Prisoner’s Dilemma. Both evolutionary simulation and mathematical analysis indicate that the proposed metric-based routing protocol is an efficient technique in promoting evolution and stability of the IoT network.

https://irojournals.com/itdw/V3/I2/01.pdf

Metric Routing Protocol for Detecting Untrustworthy Nodes for Packet Transmission

Wireless sensor networks (WSN) have been among the most prevalent wireless innovations over the years exciting new Internet of Things (IoT) applications. IoT based WSN integrated with Internet Protocol IP allows any physical objects with sensors to be connected ubiquitously and send real-time data to the server connected to the Internet gate. Security in WSN remains an ongoing research trend that falls under the IoT paradigm. A WSN node deployed in a hostile environment is likely to open security attacks such as Sybil attack due to its distributed architecture and network contention implemented in the routing protocol. In a Sybil attack, an adversary illegally advertises several false identities or a single identity that may occur at several locations called Sybil nodes. Therefore, in this paper, we give a survey of the most up-to-date assured methods to defend from the Sybil attack. The Sybil attack countermeasures includes encryption, trust, received signal indicator (RSSI), encryption and artificial intelligence. Specifically, we survey different methods, along with their advantages and disadvantages, to mitigate the Sybil attack. We discussed the lesson learned and the future avenues of study and open issues in WSN security analysis.

A survey of Sybil attack countermeasures in IoT-based wireless sensor networks.

In the article, we present the research and development of an improved delay-sensitive routing tensor model for the core of the IoT network. The flow-based tensor model is considered within the coordinate system of interpolar paths and internal node pairs. The advantage of the presented model is the application for IoT architectures to ensure the Quality of Service under the parameters of bandwidth, average end-to-end delay, and the probability of packet loss. Hence, the technical task of delay-sensitive routing is formulated as the optimization problem together with constraints and conditions imposed on the corresponding routing variables. The system of optimality criteria is chosen for an investigation. Each selected criterion concerning the specifics of the demanded routing problem solution aims at the optimal use of available network resources and the improvement of QoS indicators, namely, average end-to-end delay. The analysis of the obtained routing solutions under different criteria is performed. Numerical research of the improved delay-sensitive routing tensor model allowed us to discover its features and proved the adequacy of the results for the multipath order of routing.

https://www.mdpi.com/1424-8220/21/11/3934/pdf

Research and Development of Delay-Sensitive Routing Tensor Model in IoT Core Networks.

In the industrial Internet of things (IIoT), there is always a strong demand for real-time information transfer. Especially when deploying wireless/wired hybrid networks in smart factories, the requirement for low delay interaction is more prominent. Although tree routing protocols have been successfully executed in simple networks, more challenges in transmission speed can be observed in the manufacturing broadband communication system. Motivated by the progresses in deep learning, a smart collaborative routing protocol with low delay and high reliability is proposed to accommodate mixed link scenarios. First, we establish a one-hop delay model to investigate the potential affects of Media Access Control (MAC) layer parameters, which supports the subsequent design. Second, forwarding, maintenance, and efficiency strategies are created to construct the basic functionalities for our routing protocol. Relevant procedures and key approaches are highlighted as well. Third, two sub-protocols are generated and the corresponding implementation steps are described. The experimental results demonstrate that the end-to-end delay can be effectively cut down through comprehensive improvements. Even more sensor nodes and larger network scale are involved, our proposed protocol can still illustrate the advantages comparing with existing solutions within IIoT.

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Nan Wang

Papers

A Smart Collaborative Routing Protocol for Delay Sensitive Applications in Industrial IoT