An energy-balanced unequal clustering approach for circular wireless sensor networks

Zhao, Chengkun; Wu, Qian; Lin, Deyu; Zhang, Zhiqiang; Zhang, Yujie; Kong, Linghe; Guan, Yong Liang

doi:10.1016/j.adhoc.2022.102872

Cited by 15 publications

(7 citation statements)

References 37 publications

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“… Network lifetime: Uneven clustering has the primary purpose of enhancing the network's lifetime, which is essential for all the real-time applications that require energy conservation among the nodes of the WSNs due to the limited amount of energy available. A good routing algorithm and rotating CPUs can be used to conserve energy with uneven clustering [27,28].…”

Section: Objectivementioning

confidence: 99%

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

Zhang¹

2023

IJACSA

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The low-cost and convenient feature of Wireless Sensor Networks (WSNs) has made them popular in many sectors over the last decade. The WSNs are now widely used as a result of recent advancements in low-power communication and being energy-efficient. The WSNs typically use batteries to power sensor nodes. The finite stored energy in batteries and the hassle of battery replacement have led to a critical focus on energy efficiency for WSNs. Clustering and data aggregation are the most efficient methods to address the energy concerns of WSNs. This paper comprehensively reviews several uneven clustering methods and compares the various uneven clustering algorithms. The methods are described in terms of their goals, attributes, categories, advantages and disadvantages. Probabilistic clustering is used when there is a need of simplicity and speed. As a result, this study compared all these types of protocols based on their clustering properties, CHs properties, and on the type of clustering process; and current research gap effective techniques are also addressed.

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Section: Objectivementioning

confidence: 99%

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

Zhang¹

2023

IJACSA

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“…They are selectively activated from next‐round sensor nodes to monitor the target continuously, and in this Gini index is used for energy consumption. In Reference 60, the author proposed EBCA (Energy balance un‐equal clustering approach), which is based on the gradient for optimal cluster heads and aims to balance energy consumption in the whole network. Here fuzzy logic‐based cluster head rotation is also proposed to balance the distribution of energy consumption.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy based multi‐criteria based cluster head selection for enhancing network lifetime and efficient energy consumption

Srivastava,

Mishra

2023

Concurrency and Computation

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SummarySensors plays an important role in day‐to‐day life as they sense and transfer data on the cloud and servers. These sensors have limited battery power due to which their optimized use is preferred with efficient energy consumption. As sensors were deployed almost everywhere under‐earth, underwater, electronic devices, and mobiles thus their enhanced performance is really important. In WSN, clustering is considered to be an essential approach that gives various advantages such as efficient energy, stability period, network lifetime, less delay, and scalability but has an issue of hot‐spot or energy‐hole problems. For this Un‐Equal Clustering is proposed where the size of clusters varies directly to the distance of the B.S. (Base Station). The main objective of Un‐Equal clustering is energy consumption, hot‐spot problem, and load balance among the cluster heads. In this paper, we have proposed an improved fuzzy‐based multi‐attributes un‐equal clustering to overcome the problem of hot‐spot problem. Earlier, researchers considered two attributes for selecting cluster heads (CHs), but later some of the MADM approaches were used that considered multiple attributes for optimal cluster head selection. In this paper, we have applied the fuzzy‐based TOPSIS method for optimized Un‐Equal clustering where the optimal node deployments with load balance among sensor nodes having optimal coverage and connectivity is considered. The results of the proposed method validate that it is one of the effective ways for selecting optimal cluster heads using fuzzy‐based multi‐attributes. Fuzzy‐based TOPSIS for cluster heads selection method shows 37% enhanced network performance with other compared existing algorithms. The performance of the proposed method is evaluated in terms of network stability, packet delivery, energy consumption, and network lifetime and F‐MAUC (Fuzzy based multi‐attributes un‐equal clustering) outperforms all other compared algorithms.

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“…Furthermore, every function block has its individual purpose. The fusion center gathers data on the channel utilization of various technologies with efficacy energy consumption 11–13 . The scheduling center determines transmission order and adjusts the priority based on the environment.…”

Section: Introductionmentioning

confidence: 99%

“…The fusion center gathers data on the channel utilization of various technologies with efficacy energy consumption. [11][12][13] The scheduling center determines transmission order and adjusts the priority based on the environment. The precise and efficient utilization of channel information is critical to CR performance.…”

mentioning

confidence: 99%

AFHO‐based link reliable routing and power‐assisted channel allocation protocol in cognitive radio networks for healthcare applications

Sekar,

Appranchi

2024

Trans Emerging Tel Tech

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In the realm of cognitive networks, accommodating the increasing need for radio spectrum to facilitate both secondary and primary users stands as an intricate and demanding task. This study introduces a tailored framework for healthcare applications in Cognitive Radio (CR) networks for link reliable routing and power‐assisted channel allocation. Through the integration of Adaptive Fire Hawk Optimization for routing, the strategy addresses optimization complexities while prioritizing robust link quality via optimal hop selection for effective communication. A new routing optimization challenge is formulated, aiming to establish reliable communication pathways and extend link reliability. Moreover, the framework incorporates power‐assisted channel allocation to strategically enhance resource management and overall network performance. The rigorous evaluation demonstrates significant enhancements across key performance metrics, which showcase percentage improvements of 9.86%, 14.56%, 3.85%, 5.06%, 6.94%, and 17.80% for active nodes, delay, Packet Delivery Ratio (PDR), residual energy, and throughput, respectively. These advancements underscore the proposed approach's efficacy in enhancing CR network performance, particularly for healthcare applications.

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An energy-balanced unequal clustering approach for circular wireless sensor networks

Cited by 15 publications

References 37 publications

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

Fuzzy based multi‐criteria based cluster head selection for enhancing network lifetime and efficient energy consumption

AFHO‐based link reliable routing and power‐assisted channel allocation protocol in cognitive radio networks for healthcare applications

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