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Coverage and Energy Efficiency Optimization for Randomly Deployed Multi-tier Wireless Multimedia Sensor Networks.

Author(s)
Taner Cevik Department of Computer Engineering, Istanbul Aydin University, Istanbul, Turkey
Alex Gunagwera Department of Computer Engineering, Istanbul Sabahattin Zaim University, Istanbul, Turkey
Abstract
In this study, a novel multi-tier framework is proposed for randomly deployed WMSNs. Low cost directional Passive Infrared Sensors (PIR sensors) are randomly deployed across a Region of Interest (RoI), which are activated according to the Differential Evolution (DE) algorithm proposed for coverage optimization. The proposed DE and the Genetic Algorithms are applied to optimize the coverage maximization using minimum sensors. Only the scalar sensors that are yielded by the coverage optimization process are kept active throughout the network lifetime while the multimedia sensors are kept in silent. When a scalar sensor detects an event, the corresponding multimedia sensor(s), in whose effective coverage field of view (FoV) that the target falls, is then activated to capture the event. The analysis of the network total energy expenditure and a comparison of the proposed framework to current approaches and frameworks is made. Simulation results show that the proposed architecture achieves a remarkable network lifetime prolongation while extending the coverage area.
Publication Details
Page(s) 28-36
DOI DOI not available
Published Journal: International Journal of Communication Networks and Information Security, Volume: 10, Issue: 1, Year: 2018

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References
I.F.Akyildiz,W.Su,Y.Sankarasubramaniam, 2002.Wireless sensor networks: a survey”, Elsevier Computer Networks, 38 393 -422
M.Ebrahim,C. W.Chong, 2014.A Comprehensive Review of Distributed Coding Algorithms for Visual Sensor Network (VSN)”,International Journal of Communication Networks and Information Security (IJCNIS) 6 104 -117
F.Frattolillo, 2016.A Deterministic Algorithm for the Deployment of Wireless Sensor Networks”,International Journal of Communication Networks and Information Security (IJCNIS) 8 1 -10
B. O.Yenke,“MMEDD, 2016.Multithreading Model for an Efficient Data Delivery in wireless sensor networks”,International Journal of Communication Networks and Information Security (IJCNIS) 8 179 -186
T.Cevik,A.Gunagwera, 2015.A Survey of Multimedia Streaming in Wireless Sensor Networks: Progress, Issues,International Journal of Computer Networks & Communications 7 95 -114
J. N.Al-Karaki,A. E.Kamal, 2004.Routing techniques in wireless sensor networks: a survey”,IEEE Wireless Communications 11 6 -28
J.Stankovic,T.Abdelzaher,C.Lu,L.Sha, 2003.Real-time communication and coordination in embedded sensor networks”,in Proceedings of the IEEE 91 1002 -1022
R. L.Haupt,S. E.Haupt, 2004., -
L.Wang, 2012.A novel modified binary differential evolution algorithm and its applications”,Neurocomputing 98 55 -75
R.Storn, 1997.Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces”,Journal of Global Optimization 11 341 -359
G.Pampara,A. P.Engelbrecht,N.Franken, 2006.Binary differential evolution”,IEEE International Conference on Evolutionary Computation 1873 -1879
S.Baluja, 1994.Population-based incremental learning: a method for integrating genetic search based function optimization and competitive learning”,Technical report CMU-CS-94-163 -
C.Yu,S.Soro, 2007.LifetimeDistortion Trade-Off in Image Sensor Networks”,IEEE International Conference on Image Processing 129 -132
M.Rahimi, 2006.“Magic Numbers in Networks of Wireless Image Sensors”, 71 -81
B.Chen,“SPAN,WirelessNetworks, 2002.An Energy Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks”, 8 481 -494
W.Ye,J.Heidemann,D.Estrin, 2002.An energy-efficient MAC protocol for wireless sensor networks”,21st Annual Joint Conference of the IEEE Computer and Communications Societies 1567 -1576
C.B. Margi, 2006.“Characterizing Energy Consumption in a Visual Sensor Network Testbed”,2nd IEEE Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities 339 -346
C.B. Margi , R.,Manduchi, 2006.Energy Consumption Tradeoffs in Visual Sensor Networks”,24th Brazilian Symposium on Computer Networks 1 -16
W.R.Heinzelman,A.Chandrakasan,HI, 2000.Energy-efficient communication protocol for wireless microsensor networks”,IEEE 33rd Annual Hawaii International Conference On System Sciences, Maui 1 -10
DatasheetC, 2006.Chipcon products,Texas Instruments -
A.Moschitta,CommunicationTechnology, 2014.Power consumption assessment in wireless sensor networks”, ICT-Energy-Concepts towards Zero-Power Information, -
C.F.Chiasserini, 2002.Energy consumption and image quality in wireless video-surveillance networks”,13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications 2357 -2361
T.Kavitha,D.Sridharan, 2013.(c) Figure 7. Performance Comparison of the method proposed and traditional approach. (a) Area Coverage Analysis (b) Sensor activation analysis. (c) Coverage fitness value vs number of iterations.,Malaysian Journal of Computer Science 26 211 -231
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