A Survey on Wireless Sensor Networks Coverage Problems

Maheshwari, Aastha; Chand, Narottam

doi:10.1007/978-981-13-1217-5_16

Cited by 35 publications

(19 citation statements)

References 25 publications

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“…The diagram of Voronoi [4], it is used to solve problems such as the deployment of sensors. In a 2D space, its goal is to maximize the coverage and lifetime of the WSN, and the virtual force that is used to address the problem of deploying sensors [5] [6].…”

Section: Related Workmentioning

confidence: 99%

3D Deployment Problem in Wireless Sensor Networks resolved by Genetic and Ant Colony Algorithms

Mnasri

Nasri

Alrashidi

et al. 2020

2020 International Conference on Computing and Information Technology (ICCIT-1441)

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Wireless Sensor Networks (WSN) is an evolving field of research with various applications. Deploying sensors is a decisive operation that greatly influences the performance and the functioning of the network. Comparing the 2D deployment with the 3D one, the latter is more complex because of its ability to attend more constraints imposed by real problems. On this article, we discuss the 3D node positioning problem, while minimizing the global number of sensors, the consumption levels of energy, and maximizing the covered area and the hybrid localization rate based on the 3D DV-HOP protocol and the RSSI. We seek to solve our problem by choosing the ideal 3D locations to add nomad nodes to achieve the mentioned objectives. An approach based on variants of optimization algorithms based on the NSGA-II algorithm [1] and the ACO algorithm [2] is proposed. The simulation model considers the implementation of the IEEE 802.15.4 standard, and a reactive AODV based routing layer. The results of simulations with OMNeT++ indicate the sustainability of the tested algorithms (NSGA-II, ACO).

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Section: Related Workmentioning

confidence: 99%

3D Deployment Problem in Wireless Sensor Networks resolved by Genetic and Ant Colony Algorithms

Mnasri

Nasri

Alrashidi

et al. 2020

2020 International Conference on Computing and Information Technology (ICCIT-1441)

View full text Add to dashboard Cite

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“…More details on the coverage problems and their resolving methods can be found on the following recent surveys: [20][21][22].…”

Section: Related Workmentioning

confidence: 99%

Improved Many-Objective Optimization Algorithms for the 3D Indoor Deployment Problem

et al. 2019

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Compared with the two-dimensional deployment, the three-dimensional deployment of sensor networks is more challenging. We studied the problem of 3D repositioning of sensor nodes in wireless sensor networks. We aim essentially to add a set of nodes to the initial architecture. The positions of the added nodes are determined by the proposed algorithms while optimizing a set of objectives. In this paper, we suggest two main contributions. The first one is an analysis contribution where the modelling of the problem is given and a set of modifications is incorporated on the tested multiobjective evolutionary algorithms to resolve the issues encountered when resolving many-objective problems. These modifications concern essentially an adaptive mutation and recombination operators with neighbourhood mating restrictions, the use of a multiple scalarizing functions concept and the incorporation of the reduction in dimensionality. The second contribution is an application one, where an experimental study on real testbeds is detailed to test the behaviour of the enhanced algorithms on a real-world context. Experimental tests followed by numerical results prove the efficiency of the proposed modifications against original algorithms.

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“…Even in the current time, the environment sensing through IoTs and other application-specific sensors are used for integration with many online forensic and real-time surveillance applications where innovative techniques are highly desirable to overcome the cybercrime issues [22]. To make the network fully connected to handle the converge Wireless Communications and Mobile Computing [23] issues due to many obstacles is also highly desirable in the protocol along with other core issues like network lifetime by ensuring energy efficiency in the network.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Zone-Based Routing with Hierarchical Routing in Wireless Sensor Networks

Jadoon

Zhou

Khan

et al. 2019

Wireless Communications and Mobile Computing

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Routing remains a most challenging task in sensor networks because of constrained resources like battery power, processing, and memory. Many energy efficiency techniques for the sensor networks have been proposed, among which hierarchical routing is considered the most energy-efficient and extended network lifetime technique. This technique has a lesser number of transmissions in the network. On the contrary, zone-based routing claims lesser control and routing overhead on the overall network lifetime. In this research, a simulation-based comparison of zone-based routing with static clustering hierarchical routing is conducted. The simulation results show that the zone-based routing outperforms hierarchical routing with static clustering in terms of energy efficiency, network lifetime, and throughput.

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A Survey on Wireless Sensor Networks Coverage Problems

Cited by 35 publications

References 25 publications

3D Deployment Problem in Wireless Sensor Networks resolved by Genetic and Ant Colony Algorithms

3D Deployment Problem in Wireless Sensor Networks resolved by Genetic and Ant Colony Algorithms

Improved Many-Objective Optimization Algorithms for the 3D Indoor Deployment Problem

Performance Evaluation of Zone-Based Routing with Hierarchical Routing in Wireless Sensor Networks

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