Optimization of Routing-Based Clustering Approaches in Wireless Sensor Network: Review and Open Research Issues

Manuel, Asha Jerlin; Deverajan, Ganesh Gopal; Patan, Rizwan; Gandomi, Amir H.

doi:10.3390/electronics9101630

Cited by 35 publications

(20 citation statements)

References 90 publications

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“…The very recent survey by Manuel et al [ 156 ] is much more complete and the classification considers both swarm intelligence algorithms: ant colony optimization (ACO), artificial bee colony optimization (ABCO), fuzzy logic (FL), genetic algorithm (GA), whale algorithm (WA), or particle swarm optimization (PSO) and methodological approaches (fuzzy-based and metaheuristic-based approaches). See Figure 5 reproduced from this complete survey.…”

Section: Energy Conservationmentioning

confidence: 99%

Current Trends on Green Wireless Sensor Networks

López-Ardao

Rodríguez-Rubio

Suárez-González

et al. 2021

Sensors

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The issue of energy balancing in Wireless Sensor Networks is a pivotal one, crucial in their deployment. This problem can be subdivided in three areas: (i) energy conservation techniques, usually implying minimizing the cost of communication at the nodes since it is known that the radio is the biggest consumer of the available energy; (ii) energy-harvesting techniques, converting energy from not full-time available environmental sources and usually storing it; and (iii) energy transfer techniques, sharing energy resources from one node (either specialized or not) to another one. In this article, we survey the main contributions in these three areas and identify the main trending topics in recent research. A discussion and some future directions are also included.

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Section: Energy Conservationmentioning

confidence: 99%

Current Trends on Green Wireless Sensor Networks

López-Ardao

Rodríguez-Rubio

Suárez-González

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Hybrid optimization approaches are classified into fuzzy-based and meta-heuristicbased methods [106]. Some nodes do not assume CH status because only one CH can be selected within their transmission range.…”

Section: Hybrid Fuzzymentioning

confidence: 99%

Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols

et al. 2021

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Recently, Wireless Sensor Network (WSN) technology has emerged extensively. This began with the deployment of small-scale WSNs and progressed to that of larger-scale and Internet of Things-based WSNs, focusing more on energy conservation. Network clustering is one of the ways to improve the energy efficiency of WSNs. Network clustering is a process of partitioning nodes into several clusters before selecting some nodes, which are called the Cluster Heads (CHs). The role of the regular nodes in a clustered WSN is to sense the environment and transmit the sensed data to the selected head node; this CH gathers the data for onward forwarding to the Base Station. Advantages of clustering nodes in WSNs include high callability, reduced routing delay, and increased energy efficiency. This article presents a state-of-the-art review of the available optimization techniques, beginning with the fundamentals of clustering and followed by clustering process optimization, to classifying the existing clustering protocols in WSNs. The current clustering approaches are categorized into meta-heuristic, fuzzy logic, and hybrid based on the network organization and adopted clustering management techniques. To determine clustering protocols’ competency, we compared the features and parameters of the clustering and examined the objectives, benefits, and key features of various clustering optimization methods.

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“…Sidhu, Sapra and Dhaliwal, Rashid and Siddique provide more information on blockchain and smart contracts in WSN malicious node detection [4]- [6]. WSNs are inherently resource-constrained and lack the requirements for blockchain applications and smart contracts [7]. To this end, Ellul and Pace [8] outlined a reference design architecture and implementation of a split virtual machine for WSNs, where the computationally intensive operations in accessing the blockchain systems are offloaded to unconstrained nodes.…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

et al. 2021

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Wireless Sensor Networks (WSNs) are broadly applied for various applications in tracking and surveillance due to their ease of use and other distinctive characteristics compelled by real-time cooperation among the sensor nodes. In WSNs, security is becoming a critical issue, as the techniques for malicious node detection adopt a one-time, centralized decision-making approach. With this paradigm, errors are difficult to avoid, and reproducibility and traceability are challenging. Hence, malicious node discovery technologies in conventional WSNs cannot assure traceability and fairness of the detection method. Herein, this paper discusses an in-depth survey of a blockchain-based approach for malicious node detection, an exhaustive examination of the integration of blockchain techniques with WSNs (BWSN), and insights into this novel concept. This survey discusses the architecture, sector-wise applications, and uses of BWSN. Moreover, this survey describes malicious node detection based on BWSN in two parts: 1) the BWSN architecture for detecting the malicious nodes and 2) the smart contract aspects in malicious node detection. Next, this survey explains the contributions of blockchain for WSN data management, which involves online information aggregation and may include auditing, event logs, and storage for information analysis and offline query processing. This survey first presents the conventional WSN solutions then the blockchain-based WSN solutions for data management. Additionally, this survey discusses the contributions of blockchain for WSN security management. It first examines the centralized WSN models for security problems, followed by a discussion of the blockchain-based WSN solutions for security management, such as offering access control, preserving information integrity, guaranteeing privacy, and ensuring WSNs' node longevity.

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Optimization of Routing-Based Clustering Approaches in Wireless Sensor Network: Review and Open Research Issues

Cited by 35 publications

References 90 publications

Current Trends on Green Wireless Sensor Networks

Current Trends on Green Wireless Sensor Networks

Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols

Blockchain-Based Wireless Sensor Networks for Malicious Node Detection: A Survey

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