NRSM: node redeployment shrewd mechanism for wireless sensor network
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ORIGINAL ARTICLE
NRSM: node redeployment shrewd mechanism for wireless sensor network Shahzad Ashraf1
· Tauqeer Ahmed1
· Sehrish Saleem2
Received: 11 May 2020 / Accepted: 5 October 2020 © Springer Nature Switzerland AG 2020
Abstract Despite numerous advantages, the challenges for wireless sensor communication always remains open due to which a continuous effort is being applied to tackle the unavoidable conditions regarding wireless network coverage. Somehow, the uncouth deployment of the sensor nodes is making the tribulation queue longer day by day which eventually has great impact over sensor coverage range. To address the issues related with network coverage and uncouth energy wastage, a sensor node redeployment-based shrewd mechanism (NRSM) has been proposed where new intended positions for sensor node are rummaged out in the coverage area. The proposed algorithm operates in two phases; in first phase it locates the intended node positions through Dissimilitude Enhancement Scheme (DES) and moves the node to new position. While second phase is called a Depuration, when the moving distance between initial and intended node position is shrewdly reduced. Further, different variation factors of NRSM such as loudness, pulse emission rate, maximum frequency, and sensing radius have been explored and related optimized parameters are identified. The performance metric has been meticulously analyzed through simulation rounds in Matlab and compared with state of art algorithms like Fruit Fly Optimization Algorithm (FOA), Jenga-inspired optimization algorithm (JOA) and Bacterial Foraging Algorithm (BFA) in terms of mean coverage range, computation time, standard deviation and network energy diminution. The performance metrics vouches the effectiveness of the proposed algorithm as compared to the FOA, JOA and BFA. Keywords Node deployment · Shrewd coverage · Position · Depuration · Emission · Diminution
1 Introduction In the era of wireless communication, the sensor network extensively prevailing its dominance and providing chances to the researcher to explore and discover the diversification in this field. In a Wireless Sensor Network (WSN) the sensor nodes are deployed to observe the surroundings events for some phenomenon of interest, process the sensed data and transmit it [1]. These sensor nodes are typically small in size with inbuilt micro-controllers and radio transceivers [2]. The fundamental issue in observing such environments is the area coverage which reflects how well the region is monitored. Coverage is usually defined as a measure of how well and
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Shahzad Ashraf [email protected]
1
College of Internet of Things Engineering, Hohai University, Changzhou, China
2
Muhammad Nawaz Sharif University of Engineering and Technology, Multan, Pakistan
how long the sensors are able to observe the physical space [3]. The quality of coverage in static sensor is significantly affected by the initial deployment location of the sensors. Unfortunately, sensor deployment cannot be performed manually in most app
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