An algorithm for enhancing coverage and network lifetime in cluster-based Wireless Sensor Networks

Osamy, Walid; Khedr, Ahmed M.

doi:10.17762/ijcnis.v10i1.2849

Cited by 5 publications

(1 citation statement)

References 20 publications

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“…The 3 − D underwater environment hydrophone deployment problem is a leading issue in sensor deployment research [17]. Although many scholars have developed high-coverage and low-complexity solutions, many algorithms are theoretical because they are based on an ideal environment; the practicality of these algorithms in complex underwater terrain environments remains to be confirmed [21]. In this paper, we roughly abstract the actual terrain, such as underwater trenches and basins, into curved surfaces from the actual underwater terrain data provided(in the actual calculation process, the deployment position of the sensor does not need to be accurately calculated, and this does not affect the calculation result).The direction of bumps in the complex terrain is calculated by the gradient direction method (called the trench, terrain such as the basin is concave terrain, and the topography of the mid-ocean ridge is convex terrain) [10], [29].…”

Section: − D Sensor Space Coverage Problemmentioning

confidence: 99%

Sensor Coverage Strategy in Underwater Wireless Sensor Networks

Du²

2020

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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This paper mainly describes studies hydrophone placement strategy in a complex underwater environment model to compute a set of "good" locations where data sampling will be most effective. Throughout this paper it is assumed that a 3-D underwater topographic map of a workspace is given as input.Since the negative gradient direction is the fastest descent direction, we fit a complex underwater terrain to a differentiable function and find the minimum value of the function to determine the low-lying area of the underwater terrain.The hydrophone placement strategy relies on gradient direction algorithm that solves a problem of maximize underwater coverage: Find the maximize coverage set of hydrophone inside a 3-D workspace. After finding the maximize underwater coverage set, to better take into account the optimal solution to the problem of data sampling, the finite VC-dimension algorithm computes a set of hydrophone that satisfies hydroacoustic signal energy loss constraints. We use the principle of the maximize splitting subset of the coverage set and the ”dual” set of the coverage covering set, so as to find the hitting set, and finally find the suboptimal set (i.e., the sensor suboptimal coverage set).Compared with the random deployment algorithm, although the computed set of hydrophone is not guaranteed to have minimum size, the algorithm does compute with high network coverage quality.

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Section: − D Sensor Space Coverage Problemmentioning

confidence: 99%

Sensor Coverage Strategy in Underwater Wireless Sensor Networks

Du²

2020

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Cluster-Based Energy Efficient Protocol for Wireless Sensor Network

Anand

Gowthami

2020

2020 International Conference on Emerging Trends in Information Technology and Engineering (Ic-Etite)

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Privacy Preserving Data Mining Approach for IoT based WSN in Smart City

Khedr¹,

Osamy²,

Salim³

et al. 2019

IJACSA

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Wireless Sensor Network (WSN) is one of the most fundamental technologies of Internet of Things (IoT). Various IoT devices are connected to the internet by making use of WSN composed of different sensor nodes and actuators, where these sensor nodes collaborate and accomplish their tasks dynamically. The main objective of deploying WSN-based applications is to make high precision real-time observations, and it is extremely challenging because of the limited computing power of the sensors operating under constrained environments, resource constraints like energy, computation speed, bandwidth and memory, huge volume of high speed, heterogeneous and fast-changing WSN data. These challenges encouraged the researchers to concentrate deeper on exploring data mining techniques to extract the required information from the fast-changing sensor data in WSN and thereby efficiently handle the massive data generated by the WSNs. The increasing need of data mining techniques for WSN has inspired us to propose a distributed data mining technique that effectively handles the data generated by the nodes in the WSN and prolongs the lifespan of the network. Our work provides a novel cluster based scheme to mine the sensors data without moving it to cluster head (CH) or base station (BS) to achieve maximum performance in a WSN environment. The basic idea of the proposed work is that local computations are performed by utilizing the computing power at each sensor node and then the minimum higher level statistical summaries are exchanged, which decreases the energy dissipation in communication as the amount of the sensor data transferred is considerably reduced, and thereby the sensor network lifetime is maximized and also preserve the privacy of the sensor data.

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An algorithm for enhancing coverage and network lifetime in cluster-based Wireless Sensor Networks

Cited by 5 publications

References 20 publications

Sensor Coverage Strategy in Underwater Wireless Sensor Networks

Sensor Coverage Strategy in Underwater Wireless Sensor Networks

Cluster-Based Energy Efficient Protocol for Wireless Sensor Network

Privacy Preserving Data Mining Approach for IoT based WSN in Smart City

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