Virtual Machine Placement for Edge and Cloud Computing

Partovi, Behdad; Bagheri, Alireza; Kazarji, Maryam Haddad; Pahl, Claus; Barzegar, Hamid Reza

doi:10.1007/978-3-030-71906-7_5

Cited by 1 publication

(3 citation statements)

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“…Such algorithms cannot discover near‐optimal solutions to difficult situations 69 . Because schedule optimization is one of the difficult issues, meta‐heuristic techniques should be used to discover nearly optimum solutions 47 …”

Section: Resultsmentioning

confidence: 99%

“…69 Because schedule optimization is one of the difficult issues, meta-heuristic techniques should be used to discover nearly optimum solutions. 47 For tackling the VMP issue, various studies suggest employing nature-inspired and meta-heuristics algorithms like GA, PSO, shark optimization method, imperialist competitive algorithm, and world cup optimization algorithm.…”

Section: Resultsmentioning

confidence: 99%

“…Barzegar 47 presented an energy‐aware meta‐heuristic scheduling technique for real‐time VMs. The algorithm's major purpose was to reduce the overall busy time of PMs in a given period while staying within the VMs' deadline.…”

Section: Vmp In Cloud Computingmentioning

confidence: 99%

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Nature‐inspired virtual machine placement mechanisms: A systematic review

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Abnoosian

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Cloud data centers do not completely use their resources, resulting in resource underutilization. Cloud computing companies primarily leverage virtualization technologies to supply cost-effective service provision. In order to optimize cloud performance, virtual machines (VMs) must be placed among physical machines (PMs). When it comes to concentrating on the issues in the cloud computing environment, effective VM placement (VMP) is one of the primary difficulties that might cost suppliers money. VMP may be applied in a variety of ways in cloud computing. In terms of lowering related processing overhead, consolidating the cloud environment to become a highly on-demand method, balancing the load among PMs, power usage, and refining performance, VMP techniques still require improvement in the computing environment. This study aims to provide a comprehensive overview of VMP approaches. This article provides an up-to-date survey of the most related VMP literature to highlight study possibilities in cloud settings utilizing nature-inspired metaheuristic algorithms. The findings suggest that placing VMs in the most efficient place saves power usage substantially. The key problem is to minimize data center energy usage without compromising performance or breaking service level agreements. Finally, we will discuss and look at what further may be accomplished in this line of science.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%