Cluster Based Intelligent Load Balancing Algorithm Applied in Cloud Computing Using KNN

Banerjee, Annwesha; Chatterjee, Gourav; Chakraborty, Debarka; Majumder, Sourav

doi:10.2139/ssrn.3503518

Cited by 3 publications

(1 citation statement)

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“…The above-mentioned techniques were not able to dynamically balance the workload in a cloud-computing environment; therefore, the machine learning approaches were introduced. There are various machine learning algorithms like K-Nearest Neighbors [86], deep neural networks [87], multi-layer perceptron [88], Simulated Annealing [89] that were used for LB in cloud environments. These approaches enable accurate and practical decision making the resource allotment to inbound requests, resulting in the selection of the most relevant applications to finish.…”

Section: Load Balancingmentioning

confidence: 99%

Energy efficiency in cloud computing data centers: a survey on software technologies

2022

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Cloud computing is a commercial and economic paradigm that has gained traction since 2006 and is presently the most significant technology in IT sector. From the notion of cloud computing to its energy efficiency, cloud has been the subject of much discussion. The energy consumption of data centres alone will rise from 200 TWh in 2016 to 2967 TWh in 2030. The data centres require a lot of power to provide services, which increases CO2 emissions. In this survey paper, software-based technologies that can be used for building green data centers and include power management at individual software level has been discussed. The paper discusses the energy efficiency in containers and problem-solving approaches used for reducing power consumption in data centers. Further, the paper also gives details about the impact of data centers on environment that includes the e-waste and the various standards opted by different countries for giving rating to the data centers. This article goes beyond just demonstrating new green cloud computing possibilities. Instead, it focuses the attention and resources of academia and society on a critical issue: long-term technological advancement. The article covers the new technologies that can be applied at the individual software level that includes techniques applied at virtualization level, operating system level and application level. It clearly defines different measures at each level to reduce the energy consumption that clearly adds value to the current environmental problem of pollution reduction. This article also addresses the difficulties, concerns, and needs that cloud data centres and cloud organisations must grasp, as well as some of the factors and case studies that influence green cloud usage.

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Section: Load Balancingmentioning

confidence: 99%