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·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667
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The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to:
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Energy-efficient wireless sensor networks for disaster management using hybrid technique
*Divya SinghCorresponding authorDivya.singh@gla.ac.inElectronics and Communication Engineering Late Shri Ganeshi Lal AgrawalDepartment of Electronics and Communication Engineering GLA UniversityMathura, Uttar Pradesh, 281406, IndiaView full profile →
, Nithya Savarimuthunithyas@srmist.edu.inDepartment of Electrical and Electronics Engineering SRM Institute of Science and Technology Ramapuram Department of Electrical and Electronics Engineering SRM Institute of Science and Technology RamapuramRamapuram, Chennai, 600089, IndiaView full profile →
, D. Nagarajuraj2dasari@gmail.comDepartment of Computer Science Engineering Sri Venkatesa Perumal College of Engineering and TechnologyPuttur, Andhra Pradesh, 517583, IndiaView full profile →
, Pellakuri Vidyullathalatha22pellakuri@gmail.comDepartment of Computer Science Engineering Koneru Lakshmaiah Education Foundation VaddeswaramGuntur, Andhra Pradesh, 522302, IndiaView full profile →
, K. Maithilidrmaithili@kgr.ac.inDepartment of Computer Science Engineering KG Reddy College of Engineering &Technology MoinabadHyderabad, Telangana, 501504, IndiaView full profile →
, M. Sasikumarpmsasi77@gmail.com; principal@cahcet.edu.inC. Abdul Hakeem College of Engineering & Technology Ranipet DistrictMelvisharam, Tamil Nadu, 632509, IndiaView full profile →
, Syed Mohd Fazal Ul-Haquefazal@manuu.edu.inDepartment of Polytechnic, Computer Science and Engineering Maulana Azad National Urdu(A Central University) GachibowliHyderabad, Telangana, 500032, IndiaView full profile →
, Muniyandy Elangovanmuniyandy.e@gmail.comDepartment of Biosciences Saveetha School of Engineering Saveetha Nagar; Department of R&D Bond Marine ConsultancyDepartment of Biosciences Saveetha School of Engineering Saveetha NagarThandalam, Tamil Nadu, 602105, IndiaView full profile →
* Corresponding author · click or hover a name for details
The paradigm of WSNs acted as a powerful source of data in real time for disaster management to make better and punctual decisions. In the proposed paper, an effort has been carried out to present a hybrid approach combining Genetic Algorithm, Artificial Neural Networks, and Particle Swarm Optimization: Investigating the Performance of WSNs and the Energy Efficiency in the Time of Tragedy. The design here will focus on optimal routing paths that will be energy-aware, with respects to robust network performance metrics such as latency, delivery ratio, drop rates, throughput, energy usage, node lifetime, overhead, and overall system efficiency. The proposed framework is evaluated by simulations in the NS2 simulator, comparing its performance against traditional PSO and GA models. Thus, the results indicate the hybrid approach greatly improves network efficiency as well as reliability. It thus proves to be an efficient approach for energy-efficient deployments of WSN in applications related to disaster management.
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