A Novel Method for Clustering in WSNs via TOPSIS Multi-criteria Decision-Making Algorithm

Shelebaf, Ahmad; Tabatabaei, Shayesteh

doi:10.1007/s11277-020-07087-7

Cited by 15 publications

(10 citation statements)

References 14 publications

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“…Technique for order preference by similarity to ideal solution (TOPSIS) in 1981 was proposed by Yoon & Hwang (Shelebaf and Tabatabaei, 2020), (Karami, 2011), (Hajji et al, 2018). In TOPSIS each multi-metric problem is tackled geometrically.…”

Section: Topsis Methods On Wise Routementioning

confidence: 99%

“…(See figure below) (Shelebaf and Tabatabaei, 2020). In this method, attributes are ordered with n alternatives in a matrix.…”

Section: Topsis Methods On Wise Routementioning

confidence: 99%

“…Taking the same scheme in another attempt (Shelebaf and Tabatabaei, 2020) TOPSIS is evaluated with other protocols such as IEEE802.15.4. some crucial parameters are inserted into TOPSIS such as distance from sink, neighborhood, the remaining energy, and organize and carry out of workload.…”

Section: Related Workmentioning

confidence: 99%

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Improved Routing Algorithm in IoT Network by TOPSIS method.

Kareem

Ghafoor

2021

ZJPAS

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Low energy utilization and reliability in packet transmission are factors that seriously affect the performance of Wireless Sensor Network (WSN) and Quality of Service (QoS) in general. Regarding routing strategy, the efficient forwarding methods can cause more throughput, less packet loss with less energy usage. To this purpose multi-attribute, decision-making (MADM) methods are proposed in hop-by-hop sending data scenarios, as the most efficient methods in selecting the reliable path towards the sink node. In such a decision-making environment, various routing metrics are taken into account. This paper compares Wise Route routing protocol and modified-Wise Route (MwiseRoute) by TOPSIS with indexes (signal to noise ratio, residual energy, distance from the node, farness from the sink node) balances by self-sets weights (0.3, 0.5, 0.1,0.1) respectively. The evaluation has been tested on Mixim 3.2 in Omnet++.4.6. The result shows MwiseRoute with TOPSIS is more appropriate in gaining more throughput and significantly decreases packet drop in mac by less power drain.

show abstract

Section: Topsis Methods On Wise Routementioning

confidence: 99%

“…(See figure below) (Shelebaf and Tabatabaei, 2020). In this method, attributes are ordered with n alternatives in a matrix.…”

Section: Topsis Methods On Wise Routementioning

confidence: 99%

See 1 more Smart Citation

Improved Routing Algorithm in IoT Network by TOPSIS method.

Kareem

Ghafoor

2021

ZJPAS

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“…To optimize energy consumption in wireless sensor networks, the authors of the paper [14] presented TBCA, a new clustering method based on the TOPSIS multi-criteria decision algorithm that can consume energy while improving network throughput. The protocol proposed in this paper is simulated in the OPNET11.5 simulator using the IEEE802.15.4 standard, with a focus on power consumption, end-to-end latency, media access delay, throughput rate, probability of successful sink delivery, and loss rate.…”

Section: Related Workmentioning

confidence: 99%

Cat swarm optimization-based energy efficient target tracking in wireless sensor network

Tabatabaei¹

2023

Preprint

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Objective: using the cat swarm optimization algorithm to reduce energy consumption and data transmission delay in WSNs (wireless sensor networks) Materials and Methods: WSNs have emerged as a critical sensing technology with a wide range of military and civilian applications. In these networks, a large number of sensors are distributed throughout an area to track a specific target. Each sensor is regarded as an operating tool that uses limited energy. They can sense and understand events within their sensing domains, as well as communicate with neighbouring sensor nodes. Because the battery determines the lifespan of a sensor, an efficient method of energy consumption must be used. The depletion of batteries' limited energy reserves may result in the network's demise. As a result, devising and developing a time plan for sensors' sleep and wake-up cycles is regarded as a critical goal in line with increasing network lifetime. We proposed a novel and different time planning method for enhancing the lifetimes of WSNs in this paper, using the cat swarm optimization algorithm, in which at least half of the full coverage is provided at all times. The simulation results showed that using a cat swarm optimization algorithm can reduce energy consumption and data transmission delay. It also improves load balance. Opnet simulator version 11.5 was used for the experiments and simulation.s

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“…Although complex, this routing protocol has some variables that can be changed. For the purpose of resolving the aforementioned problems, a unique lightweight energyaware clustering method for WSNs was developed in [19]. They concentrated on clustering sensor nodes as a means for extending the lifetime of WSNs.…”

Section: Related Workmentioning

confidence: 99%

A Novel Method for Energy Efficiency in Internet of Thing (IoT) through Fuzzy Logic and Genetic-Algorithm-Based Clustering applied for Agriculture Monitoring

Tabatabaei¹

2023

Preprint

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Over the past few decades, research on the Internet of Things (IoT) has advanced quickly thanks to recent advancements in wireless communication technologies. IoT is evolving into a large-scale, all-encompassing network that will be extensively used in environmental monitoring, agriculture, and other fields. Wireless Sensor Networks (WSNs) serve as the IoT systems' primary monitoring infrastructure. WSNs could be used to monitor the conditions in an agricultural field, including temperature, humidity, light, carbon dioxide, soil moisture, and acidity. These factors have a crucial role in the development, excellence, and yield of crops. In order to gather crucial data, numerous sensor devices are placed in agricultural land. The ability of sensor nodes to conserve energy is thought to be crucial for extending the lifespan of WSNs. Innovative, effective, and cost-effective solutions should be devised to provide reasonable energy consumption and maximize the lifespan of WSNs for agricultural. In routing operations, clustering is recognized as a well-known strategy. In this paper, a novel energy-efficient approach based on genetic algorithms and fuzzy logic is suggested to increase network lifetime. The proposed technique use an integrated clustering structure to reduce the distances between sensor nodes where data must be transmitted. The results of OPNET's simulations showed that the suggested system performs better than the IEEE 802.15.4 protocol in terms of energy usage and WSN lifetime.

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A Novel Method for Clustering in WSNs via TOPSIS Multi-criteria Decision-Making Algorithm

Cited by 15 publications

References 14 publications

Improved Routing Algorithm in IoT Network by TOPSIS method.

Improved Routing Algorithm in IoT Network by TOPSIS method.

Cat swarm optimization-based energy efficient target tracking in wireless sensor network

A Novel Method for Energy Efficiency in Internet of Thing (IoT) through Fuzzy Logic and Genetic-Algorithm-Based Clustering applied for Agriculture Monitoring

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