Power consumption management system (PCMS) in wired networks using adaptive genetic algorithm
| dc.contributor.author | Choudhary, Rajkumar | |
| dc.contributor.author | Perinpanayagam, Suresh | |
| dc.date.accessioned | 2022-10-03T11:21:29Z | |
| dc.date.available | 2022-10-03T11:21:29Z | |
| dc.date.issued | 2022-08-10 | |
| dc.description.abstract | Power consumption in both wired and wireless networks is becoming an increasingly important concern across the world. Most scholars have concentrated on wireless, so we have taken wired networks as our focus. Wired network operators had an increased network concern to meet the decrease in traffic levels from which service quality (QoS) is achieved and maximize power consumption. To achieve the QOS and power consumption in a wired network, we provided comprehensive Power Consumption Management (PCMS) research modules that provide current and future access networks. The results of PCMS are being tested out with the genetic algorithm gives us the best-optimized module. | en_UK |
| dc.identifier.citation | Choudhary R & Perinpanayagam S (2022) Power consumption management system (PCMS) in wired networks using adaptive genetic algorithm. In: 2022 IEEE Aerospace Conference, 5-12 March 2022, Big Sky, MT, USA | en_UK |
| dc.identifier.eisbn | 978-1-6654-3760-8 | |
| dc.identifier.isbn | 978-1-6654-3761-5 | |
| dc.identifier.issn | 1095-323X | |
| dc.identifier.uri | https://doi.org/10.1109/AERO53065.2022.9843332 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/18503 | |
| dc.language.iso | en | en_UK |
| dc.publisher | IEEE | en_UK |
| dc.rights | Attribution-NonCommercial 4.0 International | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.subject | wired network | en_UK |
| dc.subject | power consumption management (PCM) | en_UK |
| dc.subject | power consumption | en_UK |
| dc.subject | QoS | en_UK |
| dc.subject | Genetic algorithm | en_UK |
| dc.title | Power consumption management system (PCMS) in wired networks using adaptive genetic algorithm | en_UK |
| dc.type | Conference paper | en_UK |
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