Energy Efficient Coverage Problems in Wireless Ad Hoc Sensor Networks

Anand, Darpan; Chandrakanth, H. G.; Giriprasad, M. N.

doi:10.5121/acij.2011.2204

Cited by 15 publications

(8 citation statements)

References 19 publications

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“…In this field, UAVs have a lot of potential [10,19]: drone based wireless sensors networks (WSNs) are developed for a wide variety of applications (e.g., health-care and environmental monitoring [5,[46][47][48][49][50][51]). With advances in the field of autonomous intelligent systems, and given the progress made with mobile cyber-physical systems, building and deploying mobile WSNs (where individual nodes can move and are endowed with computational power to enable information driven self-organization and on-board reasoning and decision making) is becoming increasingly common [17,.…”

Section: Reference Wan Rs Rtm Sar Gl Int Simentioning

confidence: 99%

A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

Eledlebi

Hildmann

Ruta

et al. 2020

Drones

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Using autonomously operating mobile sensor nodes to form adaptive wireless sensor networks has great potential for monitoring applications in the real world. Especially in, e.g., disaster response scenarios—that is, when the environment is potentially unsafe and unknown—drones can offer fast access and provide crucial intelligence to rescue forces due the fact that they—unlike humans—are expendable and can operate in 3D space, often allowing them to ignore rubble and blocked passages. Among the practical issues faced are the optimizing of device–device communication, the deployment process and the limited power supply for the devices and the hardware they carry. To address these challenges a host of literature is available, proposing, e.g., the use of nature-inspired approaches. In this field, our own work (bio-inspired self-organizing network, BISON, which uses Voronoi tessellations) achieved promising results. In our previous approach the wireless sensors network (WSN) nodes were using knowledge about their coverage areas center of gravity, something which a drone would not automatically know. To address this, we augment BISON with a genetic algorithm (GA), which has the benefit of further improving network deployment time and overall coverage. Our evaluations show, unsurprisingly, an increase in energy cost. Two variations of our proposed GA-BISON deployment strategies are presented and compared, along with the impact of the GA. Counter-intuitively, performance and robustness increase in the presence of noise.

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Section: Reference Wan Rs Rtm Sar Gl Int Simentioning

confidence: 99%

A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

Eledlebi

Hildmann

Ruta

et al. 2020

Drones

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“…Any sensor's node can be shut down for any time for network's service life. In this paper, practical detection method to schedule turns off or start sensor from nodes adaptive sleep [16]. There is specific detection methods are working for following:…”

Section: Redundant Nodes Detectingmentioning

confidence: 99%

Enhancing Multi-Objective Optimization for Wireless Sensor Networks Coverage using Swarm Bat Algorithm

Saleh¹

2017

IJCA

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Coverage area in wireless sensor network (WSN) is very important for network's performance.it has several critical and challenges that are to be occupied when designing the techniques and algorithms to increase the Network lifetime. Therefore WSN poses problem involve exchange data between multiple conflicting optimization objectives such as coverage preservation. The proposed paper applies new approach to optimize the coverage performance of WSN. The algorithm strategy new multi-objective optimization bat swarm algorithm with adaptive neighborhood processes and turnoff redundant sensor nodes. Any position of mobile sensor nodes represented by bat which is used in hybrid bat algorithm.The algorithm is presented an adaptive neighborhood which can successfully avoid possibility the turnoff redundant sensor. Simulation results show that experimental results can able to improve coverage of WSN, increase the time life of network and low energy consumption

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“…When using a mobile element, the technique used to select a CH must be mobility aware. An algorithm is proposed [16] [49] that is responsive to this. It is based on the following principles:…”

Section: Mobile Element Path Generationmentioning

confidence: 99%

“…Coverage is interpreted as how a sensor network will monitor a field of interest. There are numerous coverage problems including k-coverage, area coverage, and m-connected k-coverage problems [49]. An area coverage problem is to find a minimum number of sensor nodes to work in a given physical point and make sure that the area is monitored by at least an active (working) sensor.…”

Section: Voronoi Diagramsmentioning

confidence: 99%

Zone based hybrid approach for clustering and data collection in wireless sensor networks

Dayananda

Straub

2017

2017 International Conference on Electronics, Communications and Computers (CONIELECOMP)

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A wireless sensor network (WSN) is a collection of spatially distributed autonomous sensor nodes that can be used to monitor, among other things, environmental conditions. WSN nodes are constrained by their limited energy supply, communication range and local computational capabilities. Data routing is an area that can be optimized to allow nodes to conserve energy, improving the network's overall lifetime. Though many routing protocols can be used, using a clustering protocol can play an important role in conserving WSN energy.A new hybrid algorithm is proposed which incorporates both distributed and centralized algorithms for selection of the cluster head (CH). In most networks, sensor nodes have limited energy, so a mobile data collector (MDC) is used to collect information, reducing energy requirements. The performance of proposed algorithm is evaluated using NS-2 simulations. The results show that proposed algorithm has better performance, throughput, network lifetime compared to existing routing protocols.iv ACKNOWLEDGEMENTS

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Energy Efficient Coverage Problems in Wireless Ad Hoc Sensor Networks

Cited by 15 publications

References 19 publications

A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

Enhancing Multi-Objective Optimization for Wireless Sensor Networks Coverage using Swarm Bat Algorithm

Zone based hybrid approach for clustering and data collection in wireless sensor networks

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