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Enhancing the energy efficiency for prolonging the network life time in multi-conditional multi-sensor based wireless sensor network
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作者 Raviteja Kocherla M.Chandra Sekhar Ramesh Vatambeti 《Journal of Control and Decision》 EI 2023年第1期72-81,共10页
A wireless sensor network is one of the networks that is highly demanding by various real-timenetworking applications nowadays. A huge amount of sensor nodes is deployed in the networkrandomly and distributed. Most of... A wireless sensor network is one of the networks that is highly demanding by various real-timenetworking applications nowadays. A huge amount of sensor nodes is deployed in the networkrandomly and distributed. Most of the applications using wireless sensor network (WSN) aresurveillance monitoring applications like a forest, home, healthcare, environment, and remotemonitoring systems. Based on the application usage, the type of sensor, a number of sensornodes are deployed in such a manner where the sensors can be used effectively. But the sensornodes are restricted in the battery and sensing region. Thus, the battery of the sensor nodesis decreased based on the nodes’ function. The energy level of the sensor nodes highly affectsthe network lifetime. Improving the energy efficiency in WSN is one of the most important challengingtasks. Most of the earlier research works have proposed various methods, techniques,and routing protocols, but they are application dependent and as a common method. So, thispaper is motivated to propose a Multi-Conditional Network Analysis (MCNA) framework for savingthe energy level of the sensor nodes by reducing energy consumption. TheMCNAframeworkinvolves two different clustering processes with cluster head selection, choosing the best nodesbased on the signal strength, and the best route for data transmission. The data transmissionis done by cluster based on source-destination based. The simulation results proved that theproposed MCNA framework outperforms the other existing methods. 展开更多
关键词 Wireless sensor networks energy efficiency CLUSTERING signal strength verification
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