Energy-Efficient Routing Protocol Based on Multi-Threshold Segmentation in Wireless Sensors Networks for Precision Agriculture

Yao, Yindi; Li, Xiong; Cui, Yanpeng; Wang, Jiajun; Wang, Chen

doi:10.1109/jsen.2022.3150770

Cited by 35 publications

(12 citation statements)

References 31 publications

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“…In Reference 56 author has proposed modern meta‐heuristics algorithms based on distributed Nano‐sensors for clustering to provide efficient communication between Nano‐sensors by selecting cluster heads in IoNT (INTERNET OF NANO THINGS). In Reference 57 author has proposed an energy‐efficient routing protocol to improve the rationality of cluster formation and cluster head selection. Furthermore, a novel cluster head selection algorithm based on residual energy and optimal distance for efficient energy consumption has been proposed.…”

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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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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“…If we assume this cluster area is a circle with radius R = M/ √ π K . The expected squared distance from cluster members to the cluster head (assumed to be at the center of mass of the cluster) is given by (6).…”

Section: Node Energy Consumption and Optimal Cluster Head Numbermentioning

confidence: 99%

“…It is a self-organizing network composed of low-power micro sensor nodes, which can perform wireless communication, data sensing, processing and storage for IoT applications. However, sensor nodes are usually powered by batteries with limited capacity [5] and deployed in harsh natural environments [6], which makes it difficult to charge, let alone replace batteries. Once the node dies because of energy exhaustion, it will bring irreparable disasters to the whole network such as incomplete monitoring data and great changes of network topology will lead to decision delay or error.…”

mentioning

confidence: 99%

“…Therefore, designing an energy-efficient routing protocol is a key issue to prolong the network lifetime. Clustering routing protocol is envisioned as a promising solution [6], [9], becoming one of the research hotspots of WSNs routing protocol because of its strong scalability, low load and energy consumption, and support for data fusion. In the cluster routing protocol, all nodes are divided by clusters, and a certain node in the cluster is elected as the cluster head.…”

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confidence: 99%

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Game Theory and Coverage Optimization Based Multihop Routing Protocol for Network Lifetime in Wireless Sensor Networks

Yao

Cui

et al. 2022

IEEE Sensors J.

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Wireless sensor networks (WSNs) are selforganizing monitoring networks with a large number of randomly deployed micro sensor nodes to collect various physical information so as to realize tasks such as intelligent perception, efficient control and decision-making. However, WSNs nodes are powered by batteries, so they will run out of energy after a certain time. This energy limitation will greatly constrain the network performance like network lifetime and energy efficiency. In this study, for the purpose of prolonging network lifetime, we proposed a multi-hop routing protocol based on game theory and coverage optimization (MRP-GTCO). Briefly, in the stage of setup, two innovational strategies including clustering game with penalty function and cluster head coverage set were designed to realize the uniformity of cluster head distribution and improve the rationality of cluster head election. In the data transmission stage, we firstly derived the applicable conditions theorem of intercluster multi-hop routing. Based on this, a novel multi-hop path selection algorithm related to residual energy and node degree was proposed to provide an energy-efficient data transmission path. The simulation results showed that MRP-GTCO protocol can effectively reduce the network energy consumption and extend the network lifetime 159.22%, 50.76% and 16.46% compared with LGCA, RLEACH and ECAGT protocols.

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“…Even so, a huge amount of work was needed to analyze their concerns regarding privacy and protection. RFID systems [12,13], mainstream marketplace UbiComp devices [14], residential robots [15] and implantable medical products [16] are the devices being tested.…”

Section: Introductionmentioning

confidence: 99%

A Blockchain-Based Mutual Authentication Method to Secure the Electric Vehicles’ TPMS

Razmjoui

Kavousi‐Fard

Jin

et al. 2024

IEEE Trans. Ind. Inf.

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NOMENCLATURE Indices𝑆𝑄𝑁 𝑅 Random number created by RF receiver 𝑆𝑄𝑁 𝑆 Random number created by WE sensor 𝑆𝑄𝑁 𝑃 Random number created by TPMS Receiver 𝑈𝐼𝐷 𝑁 Present session pseudonym 𝑈𝐼𝐷 𝑂 Previous session pseudonym 𝑆𝐾 𝑁 Present session secret-key (SK) 𝑆𝐾 𝑂 Pseudonym for latest session secret -key (SK) ℎ𝑎𝑠ℎ SHA(256)

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Energy-Efficient Routing Protocol Based on Multi-Threshold Segmentation in Wireless Sensors Networks for Precision Agriculture

Cited by 35 publications

References 31 publications

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

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

Game Theory and Coverage Optimization Based Multihop Routing Protocol for Network Lifetime in Wireless Sensor Networks

A Blockchain-Based Mutual Authentication Method to Secure the Electric Vehicles’ TPMS

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