Spectrum-aware bio-inspired routing in cognitive radio sensor networks for smart grid applications

Fadel, Etimad; Faheem, Muhammad; Güngör, Vehbi Çağrı; Nassef, Laila; Akkari, Nadine; Malik, M. G. Abbas; Almasri, Suleiman; Akyildiz, Ian F.

doi:10.1016/j.comcom.2016.12.020

Cited by 67 publications

(27 citation statements)

References 17 publications

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“…The proposed routing protocol considerably decreases the data packet collision and enhances the packet delivery ratio, network throughput, energy utilization, and e2e delay in the network. The work of Fadel et al 28 presented a bio-inspired multichannel routing scheme in cognitive radio sensor network to optimize e2e reliable data packet transmission for SG applications. The suggested scheme performs well in terms of network delay, packet delivery ratio, and network throughput in a specific SG environment.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (28) assures that the intermediate sensors avoid data path loops during forwarding information in the network. ∑ S ∈( )…”

Section: Routing Mechanismmentioning

confidence: 99%

“…In addition, the performance evaluation of our designed scheme is measured by using a discrete-event network simulator, namely EstiNet9.0, 38 with the recent published bio-inspired routing scheme known as Energy and Quality Aware Spectral Honey bee inspired Clustering (EQSHC) 28 for SG applications. In fact, for real-time event monitoring applications, we compute the performance of our designed scheme in terms of PDR, which is measured as the ratio of generated packets in the network to the packets received successfully at the sink.…”

Section: Path Loss Model and Simulation Parametersmentioning

confidence: 99%

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Bio‐inspired routing protocol for WSN‐based smart grid applications in the context of Industry 4.0

Faheem

Butt

Raza

et al. 2018

Trans Emerging Tel Tech

Self Cite

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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 ...

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Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (28) assures that the intermediate sensors avoid data path loops during forwarding information in the network. ∑ S ∈( )…”

Section: Routing Mechanismmentioning

confidence: 99%

Section: Path Loss Model and Simulation Parametersmentioning

confidence: 99%

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Bio‐inspired routing protocol for WSN‐based smart grid applications in the context of Industry 4.0

Faheem

Butt

Raza

et al. 2018

Trans Emerging Tel Tech

Self Cite

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“…Honey Bee Mating Optimization (HBMO) is considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of marriage in real honey-bee [23]. In [24], it is used in routing problem in cognitive radio sensor networks.…”

Section: Si-based Algorithmsmentioning

confidence: 99%

Towards a Reference Architecture for Swarm Intelligence-Based Internet of Things

Zedadra

Savaglio

Jouandeau

et al. 2018

Internet and Distributed Computing Systems

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The Internet of Things (IoT) represents the global network which interconnects digital and physical entities. It aims at providing objects with intelligence that allows them to perceive, decide and cooperate with other objects, machines, systems and even humans to enable a whole new class of applications and services. Agent-Based Computing paradigm has been exploited to deal with the IoT system development. Many research works focus on making objects able to think by themselves thus imitating human brain. Swarm Intelligence studies the collective behavior of systems composed of many individuals who interact locally with each other and with their environment using decentralized and selforganized control to achieve complex tasks. Swarm intelligence-based systems provide decentralized, self-organized and robust systems with consideration of coordination frameworks. We explore in this paper the exploitation of swarm intelligence-based features in IoT-based systems. Therefore, we present a reference swarm-based architectural model that enables cooperation among devices in IoT systems.

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“…While a data capacity-aware channel assignment (DCA) and fish bone routing (FBR) algorithm for wireless sensor network-based smart grid applications was proposed by [21]. Also, [22] presented honey bee mating optimization-based routing and cooperative channel assignment algorithms that address QoS requirements of most smart grid operations. However, the review on the role of smart grid in renewable energy [19] reports that the smart grid is not mature enough and needs more research on the same.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Based Controller with Dedicated Safety Function for Hybrid Renewable Energy System

Nnadozie

Ukachukwu

2018

JENRR

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For the dual reasons of energy security and environmental and climate preservation, there has been a global campaign for drastic reduction in the use of fossil fuels and a consequential aggressive pursuit for the development of clean energy systems. Hybrid renewable energy systems, ahead of single source renewable energy systems, promise to be an effective alternative to the use of fossil fuels. However, if hybrid renewable energy systems must effectively and reliably serve as an alternative to fossil fuel use, then improvements in the control and management of energy flow among the renewable energy supplies, energy storage components, and the load is of very vital significance. More intelligent and optimized, and easy-to-develop control techniques need to be introduced to replace already existing conventional techniques. And very importantly, extra measures have to be taken to ensure longer battery life and the overall safety of the system. This work is a design of a fuzzy logic-based control system for managing energy flow in a hybrid renewable energy system. A dedicated output was incorporated in the fuzzy controller for controlling the load connection status. The results showed that the fuzzy logic controller accurately emulated expert decisions in monitoring the battery state-of-charge and renewable energy supply capacities, and effectively determining and controlling the battery charging and discharging functions. The employment of fuzzy logic control in the system eliminated the need for complex and tedious mathematical modelling as required in conventional control methods. Thus the system was easier to develop.

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Spectrum-aware bio-inspired routing in cognitive radio sensor networks for smart grid applications

Cited by 67 publications

References 17 publications

Bio‐inspired routing protocol for WSN‐based smart grid applications in the context of Industry 4.0

Bio‐inspired routing protocol for WSN‐based smart grid applications in the context of Industry 4.0

Towards a Reference Architecture for Swarm Intelligence-Based Internet of Things

Fuzzy Logic Based Controller with Dedicated Safety Function for Hybrid Renewable Energy System

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