Energy-efficient Multi-hop Routing with Unequal Clustering Approach for Wireless Sensor Networks

Assari, Younes El; Fallah, Samia Al; Aasri, Jihane El; Arioua, Mounir; Oualkadi, Ahmed El

doi:10.5121/ijcnc.2020.12304

Cited by 9 publications

(4 citation statements)

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“…Equation ( 18) specifies that next-hop node of CH i is within range of CH i and the next-hop node is CHj. Equation (19) shows that the next-hop node of CH i is unique, namely, CHj and Equation (20) make sure that there must not be 0 or 100% weight on the objective. The fitness function can be derived by the FLHBA-CMHR method based on the subsequent parameter.…”

Section: Honey Phasementioning

confidence: 99%

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Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

Soundararajan,

Kurangi,

Basha

et al. 2024

Int J Communication

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SummaryIn the last decades, wireless sensor networks (WSNs) have appeared as an active research area owing to their high applicability in different application areas like healthcare, automation, and the military. Several issues have been encountered in the WSNs, including energy consumption, deployment of sensor nodes, routing algorithms, energy efficiency, cluster head (CH) selection, and robustness. Cluster‐based routing is one of the energy‐efficient solutions in the WSN. At the same time, the hot spot problem remains a challenging problem, which needs to be addressed in the design of energy‐efficient solutions for WSNs. Motivated by the abovementioned discussion, c The comprehensive comparison study pointed out the betterment of the FLHBA‐CMHR technique in terms of different measures. The FLHBA‐CMHR technique obtains a maximum half‐node die (HND) of 1629 nodes, while the LEACH, FUCA, URBD, DEFL, and E‐FUCA techniques attain decreased HND of 793, 1085, 1092, 1139, and 1344 nodes correspondingly.

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Section: Honey Phasementioning

confidence: 99%

“…In El Assari, 19 an energy‐effective multi‐hop routing with UEC method was devised, for creating clusters of various sizes, which is based on the distance among the sensors and BS. Balancing the power dissipation among the CHs was the aim of this technique by implementing multi‐hop transmission to the relay node to the BS.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

Soundararajan,

Kurangi,

Basha

et al. 2024

Int J Communication

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show abstract

“…The simulation results show that proposed approach EAUCF has a better performance compared to LEACH, CHEF and EEUC algorithms.Sert et al [16]proposed Two-Tier Distributed Fuzzy Logic-Based Protocol for improving the data aggregation efficiency in the two-tier sensor networks. Selection of cluster head occur on the bases of available sensor nodes connectivity and saved energy has resolved and avoids the energy consumption in the network.The simulation graphs shows that TTDFP performance better than various methods under the same network area that is assuming metrics which is used for energy-efficiency comparison and network life time of the methods.Assari et al [17] proposed an Energy-efficient Multi-hop routing with Unequal Clustering approach to save and to balance the energy usage between all network nodes. In thisthe nodes compete to be CHs based on a probabilistic model and the remaining energy of nodes.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Logic Based Zone Head Selection Algorithm for Wireless Sensor Networks

Garg¹,

Kaur²

2021

JUSST

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Hot-spots are a problem that comes in the cluster-based routing protocol that employs multi-hop communication due to this problem the energy among the sensor nodes is not balanced. The hot-spots issue requires high overhead and is prone to connectivity issues in the sensor network this can be only possible because of unequal clustering. In this method, we have to act on all the nodes of the sensor network for communication. This process consumes high system energy if the numbers of nodes are very high. To offer guaranteed connectivity, decrease high usage and complexity, a fuzzy logic-based zone divisional method has been proposed in this paper. Use fuzzy logic to create clusters and assign nodes to them to decrease the consumption of energy and the age of the network prolongation. The simulation and results section shows the outperformance of the proposed protocol, where the (LEACH) low-energy adaptive clustering hierarchy, (EAUCF) energy-aware unequal clustering fuzzy,(EAMMH) energy-aware multi-hop multi-path hierarchical, and (TTDFP) two-tier distributed fuzzy logic-based protocol for efficient data aggregation in multi-hop wireless sensor networks algorithms. The proposed algorithm has better results in terms of energy consumption minimization, and prolongation of the network lifetime.

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“…Those sensor nodes can collect data from the surroundings, process data, and communicate with each other to root the collected data to the base station (BS). Due to dense deployment and unattended environments the sensors are usually equipped with small batteries and it cannot be recharged [1]. WSN is divided into a group of clusters, each of which has manager called the cluster head (CH).…”

Section: Introductionmentioning

confidence: 99%

Zone Head Selection Algorithm Based on Fuzzy Logic for Wireless Sensor Networks

Garg¹,

Kaur²

2021

JUSST

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Clustering extends energy resources, improves scalability and preserves communication bandwidth of the network. Clustering is either categorized as static and dynamic or as equal and unequal. Hot-spots issue needs a high overhead and is prone to connectivity problems in the wireless sensor network and this can be only possible because of unequal clustering. In this paper a zone divisional method based on fuzzy logic has been proposed. This method uses a fuzzy logic to form clusters and allot nodes to them for the reduction of energy consumption, and extends the age of the sensor network. The simulation and results section shows that the outperformance of the proposed algorithm, where the (EAUCF) energy-aware unequal clustering fuzzy, (LEACH) lowenergy adaptive clustering hierarchy, (EAMMH) energy-aware multi-hop multi-path hierarchical, and (TTDFP) two-tier distributed fuzzy logic-based protocol for efficient data aggregation in multi-hop wireless sensor networks algorithms. The proposed algorithm has better results in terms of energy consumption minimization, load balancing, and prolongation of the network lifetime.

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Energy-efficient Multi-hop Routing with Unequal Clustering Approach for Wireless Sensor Networks

Cited by 9 publications

References 0 publications

Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

Fuzzy Logic Based Zone Head Selection Algorithm for Wireless Sensor Networks

Zone Head Selection Algorithm Based on Fuzzy Logic for Wireless Sensor Networks

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