Triangular fuzzy-based spectral clustering for energy-efficient routing in wireless sensor network

Nisha, U. Nilabar; Basha, A. M.

doi:10.1007/s11227-018-2357-y

Cited by 23 publications

(15 citation statements)

References 21 publications

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“…In the cluster-based routing protocol of EH-WSNs, the node-clustering method and the management of CHs remain the essential problems. In [27], a triangular, fuzzy-based, spectral cluster routing (TF-SCR) mechanism is proposed, considering the MLC of WSNs and the reliability of data transmission. The spectral clustering method is adopted to accomplish the residual-energy-based node clustering.…”

Section: Clusteringmentioning

confidence: 99%

A Novel Adaptive Cluster Based Routing Protocol for Energy-Harvesting Wireless Sensor Networks

Han

Ran

et al. 2022

Sensors

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With the various applications of the Internet of Things, research into wireless sensor networks (WSNs) has become increasingly important. However, because of their limited energy, the communication abilities of the wireless nodes distributed in the WSN are limited. The main task of WSNs is to collect more data from targets in an energy-efficient way, because the battery replacement of large amounts of nodes is a labor-consuming work. Although the life of WSNs can be prolonged through energy-harvesting (EH) technology, it is necessary to design an energy-efficient routing protocol for the energy harvesting-based wireless sensor networks (EH-WSNs) as the nodes would be unavailable in the energy harvesting phase. A certain number of unavailable nodes would cause a coverage hole, thereby affecting the WSN’s monitoring function of the target environment. In this paper, an adaptive hierarchical-clustering-based routing protocol for EH-WSNs (HCEH-UC) is proposed to achieve uninterrupted coverage of the target region through the distributed adjustment of the data transmission. Firstly, a hierarchical-clustering-based routing protocol is proposed to balance the energy consumption of nodes. Then, a distributed alternation of working modes is proposed to adaptively control the number of nodes in the energy-harvesting mode, which could lead to uninterrupted target coverage. The simulation experimental results verify that the proposed HCEH-UC protocol can prolong the maximal lifetime coverage of WSNs compared with the conventional routing protocol and achieve uninterrupted target coverage using energy-harvesting technology.

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Section: Clusteringmentioning

confidence: 99%

A Novel Adaptive Cluster Based Routing Protocol for Energy-Harvesting Wireless Sensor Networks

Han

Ran

et al. 2022

Sensors

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“…The protocol enhances the node residual energy and improves system performance. In [27], the authors proposed a triangular fuzzy spectral-based cluster routing protocol. This technique considers the maximum link capacity of WSNs and the reliability of the transmission of data.…”

Section: Related Workmentioning

confidence: 99%

FGWOA: An Efficient Heuristic for Cluster Head Selection in WSN using Fuzzy based Grey Wolf Optimization Algorithm

Narayan

Daniel

Chaturvedi

2022

Preprint

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Wireless Sensor Network (WSN) is an important component of the Internet of Things. A WSN constitutes several Sensor Nodes (SN) that sense the various changes in the atmosphere, such as humidity, temperature, pressure etc. The Sensor Node (SN) used in WSN is powered by an inbuilt battery and performs sensing and data transmission to other SN in the network. As a result, the energy of SN is critical in WSN. The intelligent models are proposed in the present time in order to solve network issues by optimizing or decreasing the overhead to improve the WSN's energy efficiency. In this paper, a Fuzzy based approach integrated with Grey Wolf Optimization Algorithm (FGWOA) is proposed that aids cluster formation to find efficient and optimal solution for choosing the aggregation points using the Cluster Heads (CHs), and determining the best optimal path for transmission of data to the network Base Station (BS). The proposed optimal selection of different aggregation points causes the node's lifetime to be maximized. The simulation performance of FGWOA show better performance compared to various existing protocols and enhanced network lifespan.

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“…To increase the energy efficiency of the network, the Wi‐Fi radios can be turned ON and OFF by applying an associative protocol with this mechanism. In Nisha and Basha, 10 pre‐processing, clustering, and post‐processing are the three steps involved in the TF‐SCR mechanism. At first, after the sensor nodes, pre‐processing is been carried out and is subjectively apportioned within the sensing area.…”

Section: Related Workmentioning

confidence: 99%

Bio‐inspired Mimosa pudica algorithm for energy‐efficient wireless video sensor networks

Murugeswari

Murugan

2020

Int J Communication

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Wireless video sensor network (WVSN) has attracted much research interest due to its multi-faceted potential applications in different fields. An energyefficient protocol is fundamental for WVSN since the network has to deal with traffic-intensive multimedia data, such as images and videos. A few issues come in front for any such setting like energy inefficiency, throughput unfairness, and low network capacity. In many cases, we need to strike a balance between required parameters or aspects, but there is no alternative to ensuring appropriate energy efficiency in the process. Keeping this in mind, this paper proposes a holistic solution named energy-efficient bio-inspired Mimosa pudica (EEBIMP) algorithm. EEBIMP for WVSN can reduce the time delay and avoid unnecessary energy consumption due to clustering the network. Our proposed algorithm has been compared with one of the most recent notable solutions, like GREENNESS (Green wiReless vidEo sENsor NEtworks uSing out-of-band Signalling), PSO (Particle Swarm Optimization), and CUCKOO search algorithm. The result shows that EEBIMP achieved 95% of energy efficiency and throughput when compared with other algorithms of GREENNESS, PSO, and CUCKOO.

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Triangular fuzzy-based spectral clustering for energy-efficient routing in wireless sensor network

Cited by 23 publications

References 21 publications

A Novel Adaptive Cluster Based Routing Protocol for Energy-Harvesting Wireless Sensor Networks

A Novel Adaptive Cluster Based Routing Protocol for Energy-Harvesting Wireless Sensor Networks

FGWOA: An Efficient Heuristic for Cluster Head Selection in WSN using Fuzzy based Grey Wolf Optimization Algorithm

Bio‐inspired Mimosa pudica algorithm for energy‐efficient wireless video sensor networks

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