2018/06/23 by Muzammil Behzad, Manal Abdullah, Behzad, Muzammil +7 · 1 citation
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #Distributed Sensor Networks and Detection Algorithms #Energy Efficient Wireless Sensor Networks #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Networking and Internet Architecture (cs.NI) #Signal Processing (eess.SP) #Smart Grid Energy Management #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1806.09980
openalex publication_date 2018/06/23 · openalex created_date 2022/09/10 · openalex updated_date 2026/07/28
In this paper, we propose a novel framework for performance optimization in\nInternet of Things (IoT)-based next-generation wireless sensor networks. In\nparticular, a computationally-convenient system is presented to combat two\nmajor research problems in sensor networks. First is the conventionally-tackled\nresource optimization problem which triggers the drainage of battery at a\nfaster rate within a network. Such drainage promotes inefficient resource usage\nthereby causing sudden death of the network. The second main bottleneck for\nsuch networks is that of data degradation. This is because the nodes in such\nnetworks communicate via a wireless channel, where the inevitable presence of\nnoise corrupts the data making it unsuitable for practical applications.\nTherefore, we present a layer-adaptive method via 3-tier communication\nmechanism to ensure the efficient use of resources. This is supported with a\nmathematical coverage model that deals with the formation of coverage holes. We\nalso present a transform-domain based robust algorithm to effectively remove\nthe unwanted components from the data. Our proposed framework offers a handy\nalgorithm that enjoys desirable complexity for real-time applications as shown\nby the extensive simulation results.\n