Area coverage in wireless sensor network by using harmony search algorithm

Panov, Stojanche; Koceski, Saso

doi:10.1109/meco.2014.6862696

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…Another disadvantage is that the diagram can be sensitive to changes in the position of the sensors, which can lead to inaccurate results. Also, Panov and Koceski [23] have solved the area coverage problem in WSNs using the HS algorithm. The HS algorithm determines the location and number of the optimal sensor nodes in this study.…”

Section: Related Workmentioning

confidence: 99%

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ECAH: A New Energy-Aware Coverage Method for Wireless Sensor Networks using Artificial Bee Colony and Harmony Search

Zhou¹,

Zhigang²

2023

IJACSA

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Wireless Sensor Networks (WSNs) offer diverse applications in the research and commercial fields, such as military applications, medical science, waste management, home automation, habitat monitoring, and environmental observation. WSNs are generally composed of a large number of low-cost, low-power, and multifunctional sensor nodes that sense, process, and communicate data. These nodes are connected by a wireless medium, allowing them to collect and share data with each other. To achieve network coverage in a WSN, a few to thousands of tiny and low-power sensor nodes should be placed in an interconnected manner. Over the last decade, deploying sensor nodes in a WSN to cover a large area has received much attention. Coverage, regarded as an NP-hard problem, is an essential parameter for WSNs that determines how the deployed sensor nodes handle each point of interest. Various algorithms have been proposed to tackle this problem. However, they often come with a trade-off between energy efficiency and coverage rate. Moreover, the scalability of the algorithms needs to be considered for large-scale networks. This paper proposes a novel energy-aware method combining Artificial Bee Colony (ABC) and Harmony Search (HS) algorithms to address the coverage problem in WSN, called ECAH. The proposed ECAH algorithm has been tested with various network scenarios and compared with other existing algorithms. The results show that ECAH outperforms the existing methods in terms of network lifetime, coverage rate, and energy consumption. Additionally, the proposed algorithm is also more robust and efficient as it can adjust to dynamic network environment changes, making it suitable for various network scenarios.

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Section: Related Workmentioning

confidence: 99%

“…The performance of the proposed method is compared with the performance of the HS [23], PSO [22], ACO [24], multiobjective GA [37], ABC [31], and hybrid PSO with DE [25] algorithms. Therefore, we considered the datasets and parameters used in these studies.…”

Section: B Datasetmentioning

confidence: 99%

ECAH: A New Energy-Aware Coverage Method for Wireless Sensor Networks using Artificial Bee Colony and Harmony Search

Zhou¹,

Zhigang²

2023

IJACSA

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“…On the other hand, PSM, which is considered more realistic and more precise than BSM, takes in practice several dependent factors instead of the sensing radius that is used in BSM. These factors have no associated uncertainty in BSM such as noises and interferences among sensors that can affect the coverage value negatively and minimize the signal intensity [61,62]. The coverage probability of PSM is shown in Figure 4 and calculated in Equation ( 12) [60].…”

Section: Categorization Of Coverage Probability Based On Psmmentioning

confidence: 99%

An Efficient Deployment Model for Maximizing Coverage of Heterogeneous Wireless Sensor Network Based on Harmony Search Algorithm

et al. 2020

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Due to the increase of Wireless Sensor Network (WSN) technologies demand, the optimal sensor node deployment is considered as one of the most important factors that directly affect the network coverage. Most researches in WSNs that solved the problem of coverage in homogeneous and heterogeneous cases are suffering from many drawbacks such as consumed energy and high cost. In this paper, we propose an efficient deployment model based on probabilistic sensing model (PSM) and harmony search algorithm (HSA) to achieve the balance between the network coverage performance and the network cost in a heterogeneous wireless sensor network (HEWSN). The HSA is used for deployment optimization of HEWSN nodes which makes a balance between the coverage and financial cost. The PSM is used to solve the overlapping problem among the sensors. The performance of the proposed model is analyzed in terms of coverage ratio and cost evaluations. The simulation results showed the capability of the proposed heterogeneous deployment model to achieve maximum coverage and a minimum number of sensors compared to homogeneous deployment. Furthermore, a comparative study with a meta-heuristic genetic-based algorithm in HEWSN has also been conducted, and its results confirm the superiority of the proposed model.

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“…Many optimization approaches have been proposed for area coverage problems. Among them, some explore the movement-assisted sensor node deployment by using mobile nodes to improve coverage quality [7,8,9,10,11,12], and these approaches are only suitable to the scenario where the sensor node is omnidirectional.…”

Section: Related Workmentioning

confidence: 99%

“…In Ref. [11], the authors propose a harmony search optimization algorithm to solve area coverage problem. A previous study in Ref.…”

Section: Related Workmentioning

confidence: 99%

An Area Coverage and Energy Consumption Optimization Approach Based on Improved Adaptive Particle Swarm Optimization for Directional Sensor Networks

Song

Xiong

2019

Sensors

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Coverage is a vital indicator which reflects the performance of directional sensor networks (DSNs). The random deployment of directional sensor nodes will lead to many covergae blind areas and overlapping areas. Besides, the premature death of nodes will also directly affect the service quality of network due to limited energy. To address these problems, this paper proposes a new area coverage and energy consumption optimization approach based on improved adaptive particle swarm optimization (IAPSO). For area coverage problem, we set up a multi-objective optimization model in order to improve coverage ratio and reduce redundancy ratio by sensing direction rotation. For energy consumption optimization, we make energy consumption evenly distribute on each sensor node by clustering network. We set up a cluster head selection optimization model which considers the total residual energy ratio and energy consumption balance degree of cluster head candidates. We also propose a cluster formation algorithm in which member nodes choose their cluster heads by weight function. We next utilize an IAPSO to solve two optimization models to achieve high coverage ratio, low redundancy ratio and energy consumption balance. Extensive simulation results demonstrate the our proposed approach performs better than other ones.

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Area coverage in wireless sensor network by using harmony search algorithm

Cited by 5 publications

References 6 publications

ECAH: A New Energy-Aware Coverage Method for Wireless Sensor Networks using Artificial Bee Colony and Harmony Search

ECAH: A New Energy-Aware Coverage Method for Wireless Sensor Networks using Artificial Bee Colony and Harmony Search

An Efficient Deployment Model for Maximizing Coverage of Heterogeneous Wireless Sensor Network Based on Harmony Search Algorithm

An Area Coverage and Energy Consumption Optimization Approach Based on Improved Adaptive Particle Swarm Optimization for Directional Sensor Networks

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