Load-Balancing Strategy: Employing a Capsule Algorithm for Cutting Down Energy Consumption in Cloud Data Centers for Next Generation Wireless Systems

• Published in: Computational intelligence and neuroscience Vol. 2023; no. 1; p. 6090282
• Main Authors: Singh, Jyoti, Chen, Jingchao, Singh, Santar Pal, Singh, Mukund Pratap, Hassan, Montaser M., Hassan, Mohamed M., Awal, Halifa
• Format: Journal Article
• Language: English
• Published: United States Hindawi 2023; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Algorithms; Analysis; Cables; Cloud Computing; Computer centers; Computers; Customer services; Data Accuracy; Data centers; Electric Power Supplies; Electronics industry; Energy consumption; Energy efficiency; Energy management systems; Energy use; Happiness; Heuristic; Infrastructure; Innovations; Middleware; New technology; Optimization; Optimization techniques; Servers; Telecommunication systems; Virtualization; Workloads; Japan; United States > US
• ISSN: 1687-5265; 1687-5273
• DOI: 10.1155/2023/6090282

Per-user pricing is possible with cloud computing, a relatively new technology. It provides remote testing and commissioning services through the web, and it utilizes virtualization to make available computing resources. In order to host and store firm data, cloud computing relies on data centers. Data centers are made up of networked computers, cables, power supplies, and other components. Cloud data centers have always had to prioritise high performance over energy efficiency. The biggest obstacle is finding a happy medium between system performance and energy consumption, namely, lowering energy use without compromising system performance or service quality. These results were obtained using the PlanetLab dataset. In order to implement the strategy we recommend, it is crucial to get a complete picture of how energy is being consumed in the cloud. Using proper optimization criteria and guided by energy consumption models, this article offers the Capsule Significance Level of Energy Consumption (CSLEC) pattern, which demonstrates how to conserve more energy in cloud data centers. Capsule optimization’s prediction phase F1-score of 96.7 percent and 97 percent data accuracy allow for more precise projections of future value.