Improvement on LEACH Protocol of Wireless Sensor Network

Xu, Wen; Xiang, Yu

doi:10.4028/www.scientific.net/amm.347-350.1738

Cited by 27 publications

(8 citation statements)

References 7 publications

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“…In the experiments, we obtain the optimal number of the clusters, the locations of the cluster heads, and the clusters of the network by FCMMFO. Moreover, we compare the FCMMFO with FCMPSO, EEFCM-DE, LEACH algorithm in light of life cycle [15], [21], [26].…”

Section: Simulation and Resultsmentioning

confidence: 99%

Energy-Efficient Clustering Algorithm in Underwater Sensor Networks Based on Fuzzy C Means and Moth-Flame Optimization Method

Fei

Bai

et al. 2020

IEEE Access

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Underwater sensor networks (UWSN) often suffers from the irreplaceable batteries and high delay of long-distance communications, thus one of the most important issues on UWSN is how to extend the lifespan of the network and balance the energy consumption of each node by reducing the transmission distances. Actually, clustering method is one of the main methods to resolve the problem. In the clustered UWSN, the major concerns are obtaining appropriate number of clusters, forming the clusters and selecting an optimal cluster head(CH) with each cluster. This paper proposes a novel hybrid clustering method based on fuzzy c means (FCM) and moth-flame optimization method (MFO) to improve the performance of the network(FCMMFO). The idea is to form energy-efficient clusters by using FCM and then use an optimization algorithm MFO to select the optimal CH within each cluster. The simulation results validate the energyefficient performance of FCMMFO in comparison with the other existing algorithms. The results clearly show the significant impact of FCMMFO on energy-efficiency in UWSN. INDEX TERMS UWSN, clustering algorithm, fuzzy C means, moth-flame optimization.

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Section: Simulation and Resultsmentioning

confidence: 99%

Energy-Efficient Clustering Algorithm in Underwater Sensor Networks Based on Fuzzy C Means and Moth-Flame Optimization Method

Fei

Bai

et al. 2020

IEEE Access

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“…LEACH, 14 the first hierarchical protocol to route wireless sensors, is a standard protocol in clustering protocols. The LEACH process consists of two stages: the selection stage 15 of the cluster head and the stable transmission phase 16 of the data. Initially, by splitting the network into several clusters, nodes are selected randomly in the cluster as the cluster head node.…”

Section: Introductionmentioning

confidence: 99%

FUCBR: Fuzzy‐based unequal clustering and bat‐based routing protocol for WSNs assisted IoT

Agrawal

Pandey

2023

Concurrency and Computation

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SummaryThe internet of things (IoT) has recently become extremely important in our lives. With the advancement in IoT, wireless sensor networks (WSNs) have gained much importance. In WSNs, the routing of clusters has gained more interest. However, there is still a problem with the hotspot. One way to address this issue is uneven clustering. In these, nodes closer to the base station have the smallest cluster size. It decreases the relay pressure of the nodes which are close to the base station. In this paper, the unequal clustering routing based on fuzzy logic and bat algorithm is proposed, that is, FUCBR. Relative intra‐cluster costs and relative inter‐cluster costs are used in a very innovative manner. Fuzzy logic is used to create unequal clusters while the bat algorithm is used for multi‐hop routing. Unequal clustering minimizes the energy utilization for the member of the clusters. A novel probability technique is implemented in the cluster‐forming process to allow cluster members to determine which cluster they wish to join. The bat algorithm's objective function is carefully chosen to optimize the cluster heads' energy usage. After simulation, it was discovered that the proposed algorithm utilizes less energy and extends the network lifespan. The simulation results show that FUCBR's performance is 30% more improved than fuzzy‐based unequal clustering algorithm, genetic algorithm based unequal clustering and routing protocol, and grey wolf optimizer‐C algorithms. It is suitable for networks that require a long life.

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“…It cannot only monitor and control all devices of the distribution network terminals in real time but also provide customers with efficient and stable power. At present, the key factor that affects the stability of power transmission in the intelligent distribution network is how to obtain the real‐time and reliable power information efficiently 1 . In the intelligent distribution network, wireless sensor network is widely used in various fields of power equipment, such as fault diagnosis, wireless remote meter reading application and online monitoring due to its unique good performance such as low energy consumption and excellent cooperation ability 2 .…”

Section: Introductionmentioning

confidence: 99%

“…At present, researchers have been able to analyze the application of wireless sensor according to the terminal distribution characteristics of intelligent distribution network and the structure of wireless sensor network, so as to carry out hierarchical design of wireless sensor network. At present, a large number of studies have given the design process of wireless sensor and other communication methods and can realize an effective connection between the information master station of intelligent distribution network and the terminal of intelligent distribution network 1,9 …”

Section: Introductionmentioning

confidence: 99%

The network of telecommunications cross‐layer cooperation control of wireless sensor communication network applied in smart distribution grid

Yuan

2020

Int J Communication

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Summary With the rapid development of artificial intelligence, the intelligent distribution network can effectively improve the overall power supply quality of the distribution system. The designed distributed power has been able to achieve an optimal operation of grid connection, while the high‐speed operation of distribution equipment can achieve effective interaction with users. At present, intelligent distribution network is widely studied and applied in power industry because of its advantages of high efficiency energy and environmental protection. Because of its unique characteristics, such as low cost and fast speed, wireless sensor network is cleverly applied in intelligent distribution network. However, wireless sensor network has some defects in energy utilization due to its large range and too many nodes. This paper presents a cross‐layer cooperative control model, which can control the real time and reliability of network power data communication through stack protocol layer. This method can learn the weight value adaptively by training the influence relationship between the parameters of each protocol layer and achieve real‐time and reliable data communication by adjusting the policy and parameters of each layer in real time. This method takes the parameters of each wireless sensor node as the unit to establish the influence relationship between each other so as to realize the connection between each node of wireless sensor network and then to control the wireless sensor network as a whole to ensure the real‐time reliability of data communication in intelligent distribution network. In this paper, a lot of simulation experiments have been done, and the results show that the proposed cross‐layer cooperative control model can control the whole wireless sensor network to achieve efficient data transmission capacity of intelligent distribution wireless sensor network.

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Improvement on LEACH Protocol of Wireless Sensor Network

Cited by 27 publications

References 7 publications

Energy-Efficient Clustering Algorithm in Underwater Sensor Networks Based on Fuzzy C Means and Moth-Flame Optimization Method

Energy-Efficient Clustering Algorithm in Underwater Sensor Networks Based on Fuzzy C Means and Moth-Flame Optimization Method

FUCBR: Fuzzy‐based unequal clustering and bat‐based routing protocol for WSNs assisted IoT

The network of telecommunications cross‐layer cooperation control of wireless sensor communication network applied in smart distribution grid

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