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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 9/2020

20.01.2020

Deployment techniques in wireless sensor networks: a survey, classification, challenges, and future research issues

verfasst von: Rahul Priyadarshi, Bharat Gupta, Amulya Anurag

Erschienen in: The Journal of Supercomputing | Ausgabe 9/2020

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Abstract

Wireless sensor networks (WSNs) have been considered as one of the fine research areas in recent years because of vital role in numerous applications. To process the extracted data and transmit it to the various location, a large number of nodes must be deployed in a proper way because deployment is one of the major issues in WSNs. Hence, the minimum number of node deployment to attain full coverage is of enormous significance for research. The prime agenda of the presented paper is to categorize various coverage techniques into four major parts: computational geometry-based techniques, force-based techniques, grid-based techniques, and metaheuristic-based techniques. Additionally, several comparisons amid these schemes are provided in view of their benefits and drawbacks. Our discussion weighs on the classification of coverage, practical challenges in the deployment of WSNs, sensing models, and research issues in WSNs. Moreover, a detailed analysis of performance metrics and comparison among various WSNs simulators is listed. In conclusion, standing research issues along with potential work guidelines are discussed.
Vorheriger Artikel Development of training environment for deep learning with medical images on supercomputer system based on asynchronous parallel Bayesian optimization
Nächster Artikel An approach toward design and development of an energy-aware VM selection policy with improved SLA violation in the domain of green cloud computing

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Metadaten
Titel
Deployment techniques in wireless sensor networks: a survey, classification, challenges, and future research issues
verfasst von
Rahul Priyadarshi
Bharat Gupta
Amulya Anurag
Publikationsdatum
20.01.2020
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 9/2020
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-020-03166-5

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