Hierarchical routing protocols for wireless sensor network: a compressive survey

Chan, Louie; Chavez, Karina Gomez; Rudolph, Heiko; Hourani, Akram

doi:10.1007/s11276-020-02260-z

Cited by 116 publications

(50 citation statements)

References 74 publications

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“…Since the relevancy of cluster-based routing, it is common to speak indistinctly of cluster-based and hierarchical routing, but strictly speaking, other types of hierarchical structures have been proposed in the literature. Recently, Chan et al [148] In chain-based hierarchical routing, the WSN is divided into chains; and a leader is chosen for every chain. Every node sends the data to the next node until the leader is reached.…”

Section: Hierarchical Routing Protocolsmentioning

confidence: 99%

“…Since the relevancy of cluster-based routing, it is common to speak indistinctly of cluster-based and hierarchical routing, but strictly speaking, other types of hierarchical structures have been proposed in the literature. Recently, Chan et al [ 148 ] survey and compare both LEACH-based clustering and these other hierarchical structures, classified into the following categories: (a) chain-based, (b) tree-based, (c) grid-based, and (d) area-based, also represented in the Figure 3 .…”

Section: Energy Conservationmentioning

confidence: 99%

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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: Hierarchical Routing Protocolsmentioning

confidence: 99%

“…Since the relevancy of cluster-based routing, it is common to speak indistinctly of cluster-based and hierarchical routing, but strictly speaking, other types of hierarchical structures have been proposed in the literature. Recently, Chan et al [ 148 ] survey and compare both LEACH-based clustering and these other hierarchical structures, classified into the following categories: (a) chain-based, (b) tree-based, (c) grid-based, and (d) area-based, also represented in the Figure 3 .…”

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

“…The reason for choosing these two methods is due to the special feature of each of the algorithms. The LEACH-SWDN algorithm takes into account the optimal number of the CH in a dynamic environment, which is also mentioned in various studies [16][17][18][19].…”

Section: The Proposed Algorithmmentioning

confidence: 99%

An improved cluster formation process in wireless sensor network to decrease energy consumption

et al. 2020

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Wireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

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“…In contrast, in hierarchical routing, sensor nodes send data to the sink on a hop‐by‐hop manner by using proper clustering and data gathering via cluster head (CH). Cluster‐based routing schemes are energy efficient and increase the network lifetime 14,15 …”

Section: Introductionmentioning

confidence: 99%

Cluster‐based data transmission scheme in wireless sensor networks using black hole and ant colony algorithms

Sefati

Abdi

Ghaffari

2021

Int J Communication

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Summary Since sensor nodes use limited battery power, sensor nodes power is considered to be a challenge and fundamental issue in wireless networks. Wireless sensor networks (WSNs) have recently used clustering‐based methods and different routing protocols in clusters which are full of sensor nodes. In this way, cluster heads (CHs), which are regarded as the selected nodes among other nodes within a given cluster, accumulate the information transmitted from their own cluster and send it to the sink. In this method, they try to control power consumption in a balanced way. In clustering method and routing among network nodes, network lifetime is enhanced which leads to achieving the best efficiency and productivity. In this paper, the optimized black hole algorithm is employed to select an optimal CH from sensor nodes. The CH selection is optimized by the free buffer of nodes, residual energy, and distance. The path between source CH and sink is identified by using ant colony optimization (ACO) algorithm. The combination of black hole algorithm and ant colony algorithm, with respect to clustering and routing, leads to the optimization of the proposed method in terms of operational criteria such as power consumption and eventually lifetime enhancement. The results obtained from simulating the proposed method in Matlab environment indicated that it has better results in comparison with other methods. The outputs of the obtained results from the proposed method indicated that it outperformed the other four comparative methods in terms of packet delivery rate and the number of transmitted packets to the CH and to the sink.

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Hierarchical routing protocols for wireless sensor network: a compressive survey

Cited by 116 publications

References 74 publications

Current Trends on Green Wireless Sensor Networks

Current Trends on Green Wireless Sensor Networks

An improved cluster formation process in wireless sensor network to decrease energy consumption

Cluster‐based data transmission scheme in wireless sensor networks using black hole and ant colony algorithms

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