EDB‐CHS‐BOF: energy and distance‐based cluster head selection with balanced objective function protocol

Darabkh, Khalid A.; Zomot, Jumana N.; Al-qudah, Zouhair

doi:10.1049/iet-com.2019.0092

Cited by 20 publications

(7 citation statements)

References 35 publications

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“… Gupta & Pandey (2016) have considered the location of BS and residual energy as clustering parameters to solve an energy hole problem in HWSNs. Darabkh, Zomot & Al-qudah ’s (2019) scheme minimises the average energy consumption and prolongs the lifetime of WSNs.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed method is similar to Capone et al (2019) and Pal et al (2020) . Compared to existing works ( Capone et al, 2019 ; Zhang et al, 2017 ; Darabkh, Zomot & Al-qudah, 2019 ; Javaid et al, 2013a ; Sarkar & Senthil Murugan, 2019 ; Kumar & Kumar, 2016 ; Mann & Singh, 2017 ; Ali, Shahzad & Khan, 2012 ; Pal et al, 2020 ), our study is distinguished by the type of algorithm. In this approach, two methods are investigated in HWSNs.…”

Section: Related Workmentioning

confidence: 99%

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A genetic algorithm-based energy-aware multi-hop clustering scheme for heterogeneous wireless sensor networks

Muthukkumar

Garg

Maharajan

et al. 2022

PeerJ Computer Science

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Background The energy-constrained heterogeneous nodes are the most challenging wireless sensor networks (WSNs) for developing energy-aware clustering schemes. Although various clustering approaches are proven to minimise energy consumption and delay and extend the network lifetime by selecting optimum cluster heads (CHs), it is still a crucial challenge. Methods This article proposes a genetic algorithm-based energy-aware multi-hop clustering (GA-EMC) scheme for heterogeneous WSNs (HWSNs). In HWSNs, all the nodes have varying initial energy and typically have an energy consumption restriction. A genetic algorithm determines the optimal CHs and their positions in the network. The fitness of chromosomes is calculated in terms of distance, optimal CHs, and the node's residual energy. Multi-hop communication improves energy efficiency in HWSNs. The areas near the sink are deployed with more supernodes far away from the sink to solve the hot spot problem in WSNs near the sink node. Results Simulation results proclaim that the GA-EMC scheme achieves a more extended network lifetime network stability and minimises delay than existing approaches in heterogeneous nature.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A genetic algorithm-based energy-aware multi-hop clustering scheme for heterogeneous wireless sensor networks

Muthukkumar

Garg

Maharajan

et al. 2022

PeerJ Computer Science

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“…Two novel CH selection protocols for WSNs, called EDB-CHS and EDB-CHS-BOF, which are key extensions of the LEACH-DT and CEED protocols, were proposed by Darabkh et al [21]. For the first proposed protocol (EDB-CHS), there are mainly two major results.…”

Section: Related Workmentioning

confidence: 99%

ERP-DDA: Event Reporting Protocol Based on Distributed Data Aggregation for Wireless Sensor Networks

Al‐Zubi¹,

Alawad²,

Kreishan³

et al. 2021

ITC

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Wireless Sensor Networks (WSNs) have a wide range of applications in human life. Accordingly, WSNs have beenthoroughly considered in research community to improve their performance and address their challenges. Eventreporting in WSNs has always been a major challenge in terms of energy consumption. Event reporting requiressensing the event and sending a reporting packet from the sensor to the centralized base station (BS). However,sensor’s energy is limited and stored in a non-rechargeable battery. Therefore, several event-reporting (or datacollection) protocols have been proposed to improve energy consumption in WSNs, and consequently, to extendtheir lifetime. In this paper, we propose an efficient event reporting protocol for WSNs called Event ReportingProtocol Based on Distributed Data Aggregation (ERP-DDA). This protocol mainly aims at reporting any event byno more than one sensor node such that energy saving is satisfied in the whole network. To achieve this goal, ERPDDAis mainly based on the following features: it is a cluster-based protocol, it is a multi-hop routing protocol, itapplies distributed data aggregation, and it employs variable clustering and cluster head selection. Simulationsshow that ERP-DDA significantly extends the lifetime of WSNs compared with other related protocols.

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“…The SNs are distributed within a geographical area known as the area of interest (AoI). Further, they cooperate with each other to carry their measured data through the network to the main node, which is called the sink node or base station (BS) [ 1 ]. A typical WSN is illustrated in Figure 1 , where a group of sensor nodes is collecting data and sending it to a central node named as a cluster head (CH).…”

Section: Introductionmentioning

confidence: 99%

“…In most cases, SNs are powered by batteries; therefore, the lifetime of each one is very restricted and based on its limited energy source. Consequently, the energy consumption is one of the most challenging issues in WSN [ 1 , 2 ]. To address this challenge, several techniques, protocols and algorithms focusing on how to optimize energy consumption, reduce transmission interference and enhance the nodes lifetime have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Optimal Cluster Head Positioning Algorithm for Wireless Sensor Networks

Khalifeh

Abid

Darabkh

2020

Sensors

Self Cite

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Wireless sensor networks (WSNs) are increasingly gaining popularity, especially with the advent of many artificial intelligence (AI) driven applications and expert systems. Such applications require specific relevant sensors’ data to be stored, processed, analyzed, and input to the expert systems. Obviously, sensor nodes (SNs) have limited energy and computation capabilities and are normally deployed remotely over an area of interest (AoI). Therefore, proposing efficient protocols for sensing and sending data is paramount to WSNs operation. Nodes’ clustering is a widely used technique in WSNs, where the sensor nodes are grouped into clusters. Each cluster has a cluster head (CH) that is used to gather captured data of sensor nodes and forward it to a remote sink node for further processing and decision-making. In this paper, an optimization algorithm for adjusting the CH location with respect to the nodes within the cluster is proposed. This algorithm aims at finding the optimal CH location that minimizes the total sum of the nodes’ path-loss incurred within the intra-cluster communication links between the sensor nodes and the CH. Once the optimal CH is identified, the CH moves to the optimal location. This suggestion of CH re-positioning is frequently repeated for new geometric position. Excitingly, the algorithm is extended to consider the inter-cluster communication between CH nodes belonging to different clusters and distributed over a spiral trajectory. These CH nodes form a multi-hop communication link that convey the captured data of the clusters’ nodes to the sink destination node. The performance of the proposed CH positioning algorithm for the single and multi-clusters has been evaluated and compared with other related studies. The results showed the effectiveness of the proposed CH positioning algorithm.

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EDB‐CHS‐BOF: energy and distance‐based cluster head selection with balanced objective function protocol

Cited by 20 publications

References 35 publications

A genetic algorithm-based energy-aware multi-hop clustering scheme for heterogeneous wireless sensor networks

A genetic algorithm-based energy-aware multi-hop clustering scheme for heterogeneous wireless sensor networks

ERP-DDA: Event Reporting Protocol Based on Distributed Data Aggregation for Wireless Sensor Networks

Optimal Cluster Head Positioning Algorithm for Wireless Sensor Networks

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