“…Therefore, IoT has various applications in the technical market such as agriculture, traffic monitoring, parking systems, logistics, smart grids, smart vehicles, smart homes, smart cities, smart security, and several others. 7,8 The advancements in IoT will form the interface between the physical and the virtual worlds for exchanging instant industrial information is seen as a real game-changer for industrial networking in the I 4.0.…”
Recently, the advences of Industry 4.0 have paved the way for a systematical deployment of the smart grid (SG) to manage continuously growing energy demand of the 21st century. This even allows the fourth stage of the industrial revolution in the power sector, which is known as the smart grid industry (SGI) 4.0. In SGI 4.0, the industrial wireless sensor networks (WSNs) and the Internet of Things are envisioned as key promising communication technologies for monitoring various SG applications due to their large-scale coverage, fault tolerance characteristics, and cost reduction. However, highly dynamic nature of the SG environments brings several unique challenges caused by systems and operating devices. This results in hampering the quality-of-service communication requirements for WSNs-based SG applications. In SGI 4.0, the routing infrastructure not only requires a reliable but also fulfills the communication requirements of diverse SG applications. Thus, a sophisticated, reliable and QoS-aware multi-hop communications network architecture enabling a real-time exchange of data for various WSNs-based SG applications is essential in SGI 4.0. Hence, this paper proposes a novel bio-inspired self-optimized butterfly mating optimization-based data gathering routing scheme called Self-optimized Intelligent routing protocol (SIRP) for WSNs-based SG applications. The extensive simulations reveal that the proposed scheme achieves its defined goals compared to existing routing schemes designed for WSNs-based applications.Trans Emerging Tel Tech. 2019;30:e3503.wileyonlinelibrary.com/journal/ett streamline management operations are connected using wired networks working over industrial protocols in traditional factories. However, compared with a wired network, the wireless networking solution plays a complementary role to empower control and management competencies of the factory elements in I 4.0. To this end, industrial wireless sensor networks (IWSNs) are envisioned as a valuable technology to realize the vision of I 4.0 because of their low-cost sensing, identifying, processing, and networking capabilities. The IWSNs provide physical industry world information to a user located in a remote location to realize distinct objectives. 10,11 The fundamental characteristics of IWSN-based networking solution in I 4.0 is to provide least maintenance cost by avoiding excessive breakdowns in a defined time interval for enabling smart production reliability and increasing economic benefits. Therefore, IWSN, with these aims, has revealed its prominence in various industrial applications, including modern agriculture, transportation, steel mills, healthcare systems, area surveillance, gas and oil industry, and many others. 12,13 The quality-of-service (QoS)-aware cooperative multihop communication in IoT-enabled smart grid (SG) is highly dependent on a number of performance metrics like coverage, scalability, stability, latency, lifetime, and complexity of the network. In IoT-enabled SG, IWSNs through IoT connect various industrial ...
“…Therefore, IoT has various applications in the technical market such as agriculture, traffic monitoring, parking systems, logistics, smart grids, smart vehicles, smart homes, smart cities, smart security, and several others. 7,8 The advancements in IoT will form the interface between the physical and the virtual worlds for exchanging instant industrial information is seen as a real game-changer for industrial networking in the I 4.0.…”
Recently, the advences of Industry 4.0 have paved the way for a systematical deployment of the smart grid (SG) to manage continuously growing energy demand of the 21st century. This even allows the fourth stage of the industrial revolution in the power sector, which is known as the smart grid industry (SGI) 4.0. In SGI 4.0, the industrial wireless sensor networks (WSNs) and the Internet of Things are envisioned as key promising communication technologies for monitoring various SG applications due to their large-scale coverage, fault tolerance characteristics, and cost reduction. However, highly dynamic nature of the SG environments brings several unique challenges caused by systems and operating devices. This results in hampering the quality-of-service communication requirements for WSNs-based SG applications. In SGI 4.0, the routing infrastructure not only requires a reliable but also fulfills the communication requirements of diverse SG applications. Thus, a sophisticated, reliable and QoS-aware multi-hop communications network architecture enabling a real-time exchange of data for various WSNs-based SG applications is essential in SGI 4.0. Hence, this paper proposes a novel bio-inspired self-optimized butterfly mating optimization-based data gathering routing scheme called Self-optimized Intelligent routing protocol (SIRP) for WSNs-based SG applications. The extensive simulations reveal that the proposed scheme achieves its defined goals compared to existing routing schemes designed for WSNs-based applications.Trans Emerging Tel Tech. 2019;30:e3503.wileyonlinelibrary.com/journal/ett streamline management operations are connected using wired networks working over industrial protocols in traditional factories. However, compared with a wired network, the wireless networking solution plays a complementary role to empower control and management competencies of the factory elements in I 4.0. To this end, industrial wireless sensor networks (IWSNs) are envisioned as a valuable technology to realize the vision of I 4.0 because of their low-cost sensing, identifying, processing, and networking capabilities. The IWSNs provide physical industry world information to a user located in a remote location to realize distinct objectives. 10,11 The fundamental characteristics of IWSN-based networking solution in I 4.0 is to provide least maintenance cost by avoiding excessive breakdowns in a defined time interval for enabling smart production reliability and increasing economic benefits. Therefore, IWSN, with these aims, has revealed its prominence in various industrial applications, including modern agriculture, transportation, steel mills, healthcare systems, area surveillance, gas and oil industry, and many others. 12,13 The quality-of-service (QoS)-aware cooperative multihop communication in IoT-enabled smart grid (SG) is highly dependent on a number of performance metrics like coverage, scalability, stability, latency, lifetime, and complexity of the network. In IoT-enabled SG, IWSNs through IoT connect various industrial ...
“…The proposed framework was implemented with the widely used operating system for IoT i.e. Contiki OS [55,56]. The evaluation was conducted using Contiki v2.7 and its built-in emulator Cooja [57].…”
Internet of Things (IoT) represent a network of resource-constrained sensor devices connected through the open Internet which are susceptible to misuse by intruders. Proliferation of IoT across diverse application domains renders their security critical to ensure normal service delivery by such infrastructures. Traditional standalone intrusion detection systems are tasked with monitoring device behaviours to identify malicious activities. These systems not only require extensive network and system resources but also cause delays in detecting a malicious actor due to unavailability of a comprehensive view of the intruder's activities. Collaboration among IoT devices enables considering knowledge from a collection of host and network devices to achieve improved detection accuracy in a timely manner. However, collaboration introduces the challenge of energy efficiency and event processing which is particularly significant for resource-constrained devices. In this paper, we present an intrusion detection framework for IoT (COLIDE) that leverages collaboration among resource-constrained sensor devices and border nodes for effective and timely detection of intruders. The paper presents a detailed description of the proposed framework along with its formal description and analysis to assess its effectiveness for a typical IoT system. We implemented the COLIDE framework with Contiki OS and conducted thorough experimentation to evaluate its performance. This evaluation demonstrates efficiency of COLIDE framework with respect to energy and processing overheads achieving effectiveness within an IoT system.
“…It is important to note here that we have used ContikiRPL implementation to evaluate Secure‐RPL ; thus, Procedure 2 is similar to that of dis_input method of ContikiRPL. Secure‐RPL is not restricted to Contiki's scope and can be incorporated in any embedded operating system that supports RPL protocol, eg, TinyOS, RIOT, Contiki, Contiki‐NG, LiteOS, etc. …”
The IPv6 Routing Protocol for Low‐Power and Lossy Networks (RPL) is the de facto routing protocol for IPv6‐based Low‐Power Wireless Personal Area Networks (6LoWPAN). In RPL protocol, DODAG Information Solicitation (DIS) messages are sent by the node to join the network. A malicious node can exploit this mechanism to send illegitimate DIS messages to the neighbor nodes to perform a DIS flooding attack. In this research paper, it is observed that the DIS flooding attack increases the control packet overhead of the network, which significantly degrades the network's performance. This further increases the power consumption of the nodes in the network. To address this problem, a mitigation scheme named Secure‐RPL is proposed. The proposed scheme mitigates significantly the effects of DIS flooding attack on the network's performance. The effectiveness of the proposed Secure‐RPL scheme is compared with standard RPL protocol. The experimental results show that Secure‐RPL detects and mitigates DIS flooding attack quickly and efficiently in both static and dynamic network scenarios, without adding any significant overhead to the nodes.
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