An Effective Relay Node Selection Technique for Energy Efficient WSN-Assisted IoT

Shukla, Anurag; Tripathi, Sarsij

doi:10.1007/s11277-020-07167-8

Cited by 33 publications

(21 citation statements)

References 46 publications

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“…Communication technologies with their capability to adapt to ever changing market requirements, have been one of the driving forces in the IoT evolution [8], [9], [10]. In the last decades, a variety of technologies and protocols have been developed, to meet the requirements of IoT applications regarding data volume, time criticality, accuracy in transmission, energy efficiency and other constraints.…”

Section: Related Workmentioning

confidence: 99%

Design Space Exploration for an IoT Node: Trade-Offs in Processing and Communication

et al. 2021

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Optimising the energy consumption of IoT nodes can be tedious due to the due to complex trade-offs involved between processing and communication. In this article, we investigate the partitioning of processing between the sensor node and a server and study the energy trade-offs involved. We propose a method that provides a trade-off analysis for a given set of constraints and allows for exploring several intelligence partitioning configurations. Furthermore, we demonstrate how this method can be used for the analysis of four design examples with traditional and CNN-based image processing systems, and we also provide an implementation of it on Matlab.

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Section: Related Workmentioning

confidence: 99%

Design Space Exploration for an IoT Node: Trade-Offs in Processing and Communication

et al. 2021

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“…The most traditional sensor networks use the CSMA protocol as medium access protocol, performing a random access to the shared medium, which leads to the possibility of collisions and interference. In general, the scalability of this type of ad hoc network is addressed with solutions based on routing and clustering, as proposed by some works such as [13] [14] [15] [16] and [17].…”

Section: B Literature Reviewmentioning

confidence: 99%

Scalability Enhancement on Software Defined Industrial Wireless Sensor Networks Over TSCH

et al. 2022

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“…For this purpose, relay nodes (RN) are the better choice that could just transmit the information from the sensor nodes, thereby strengthen the continuous data exchange between base station and sensor nodes 25 . Deployment of RN is studied in terms of two important criteria including data transmission and connectivity 34 . In terms of connectivity, placement of RN are evaluated based on two types, single‐tiered and two‐tiered 35 .…”

Section: Related Workmentioning

confidence: 99%

Swarm intelligence‐based optimal device deployment in heterogeneous Internet of Things networks for wind farm application

Anbarasi

Prassanna

et al. 2021

Int J Communication

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Summary Internet of Things (IoT) is becoming a suitable surveillance system in modern power grid, right from power generation to distribution. In the case of wind power generation application, the entire wind farm is considered completely monitored using edge devices known as IoT devices. Device deployment is a major obstacle that can be addressed for this application as unfair device deployment can lead to connectivity issue. This study has two main objectives. The first objective is to determine the optimal number of IoT devices that need to be place in the potential key elements of the wind turbines/targets for coverage assurance. The second objective is to determine the optimal number of relay devices. Spacing wind turbines several hundred meters apart brings the connectivity as a second critical issue, which can be handling by placing optimal number of relay devices. Hence, the focus of this study is to address connected target coverage problem in optimal device placement of heterogeneous IoT network for wind farm monitoring. This paper discusses in detail the swarm intelligence technique known as particle swarm optimization (PSO) to solve the connectivity issue and to minimize the cost of devices deployment. Additionally, a hybrid swarm intelligence model called hybrid PSO‐ACO (HPACO) algorithm is proposed. The main goal of this hybrid model is to reduce the number of relay devices, minimize deployment cost, and to improve network connectivity. The performance of both PSO and HPACO algorithms are validating by comparing the extensive simulation results with ant colony optimizations (ACO) algorithm and other approximation algorithm.

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An Effective Relay Node Selection Technique for Energy Efficient WSN-Assisted IoT

Cited by 33 publications

References 46 publications

Design Space Exploration for an IoT Node: Trade-Offs in Processing and Communication

Design Space Exploration for an IoT Node: Trade-Offs in Processing and Communication

Scalability Enhancement on Software Defined Industrial Wireless Sensor Networks Over TSCH

Swarm intelligence‐based optimal device deployment in heterogeneous Internet of Things networks for wind farm application

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