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Evolutionary Computing Assisted Wireless Sensor Network Mining for QoS-Centric and Energy-efficient Routing Protocol

عنوان مقاله: Evolutionary Computing Assisted Wireless Sensor Network Mining for QoS-Centric and Energy-efficient Routing Protocol
شناسه ملی مقاله: JR_IJE-33-5_010
منتشر شده در شماره 5 دوره 33 فصل در سال 1399
مشخصات نویسندگان مقاله:

R. Sunitha - PES University, Bangalore, India
J. Chandrikab - Malnad College of Engineering, Hassan, India

خلاصه مقاله:
The exponential rise in wireless communication demands and allied applications have revitalized academia-industries to develop more efficient routing protocols. Wireless Sensor Network (WSN) being battery operated network, it often undergoes node death-causing pre-mature link outage, data drop and retransmission causing delay and energy exhaustion. Furthermore, the presence of a malicious node to impacts network performance adversely. In this paper, a highly robust and efficient Evolutionary computing assisted WSN routing protocol is developed for QoS and energy-efficiency. Our proposed routing protocol encompasses two key functions Network Condition Aware Node Profiling and Malicious Node Detection (NCAMND) exploits or mines the dynamic node/network parameters to identify malicious node, and Evolutionary Computing assisted Dual-Disjoint Forwarding Path (EC-DDFP) model learns over node/network connectivity and availability information to obtain a dual-disjoint path with no-shared components to ensure QoS centric and energy-efficient routing. Simulation results affirm that the proposed routing protocol achieves higher throughput, low energy consumption, and low delay that confirm its suitability for real-time WSN systems.

کلمات کلیدی:
Wireless Sensor Network Network Mining Evolutionary Computing Network Optimization Malicious Node Detection Link, connectivity, availability Dynamic Routing

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1021731/