An energy-efficient algorithm for virtual machine placement optimization in cloud data centers

Cluster Computing, Journal Year: 2020, Volume and Issue: 23(4), P. 3421 - 3434

Published: March 24, 2020

Language: Английский

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The importance of nature-inspired meta-heuristic algorithms for solving virtual machine consolidation problem in cloud environments

Cluster Computing, Journal Year: 2021, Volume and Issue: 24(3), P. 2673 - 2696

Published: May 4, 2021

Language: Английский

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A review on the computation offloading approaches in mobile edge computing: A game‐theoreticperspective

Software Practice and Experience, Journal Year: 2020, Volume and Issue: 50(9), P. 1719 - 1759

Published: April 23, 2020

Summary In recent years, novel mobile applications such as augmented reality, virtual and three‐dimensional gaming, running on handy devices have been pervasively popular. With rapid developments of applications, decentralized edge computing (MEC) an emerging distributed paradigm is developed for serving them near the smart devices, usually in one hop, to meet their computation, delay requirements. literature, offloading mechanisms are designed execute MEC environments through transferring resource‐intensive tasks servers. On other hand, due resource limitations, heterogeneity, dynamic nature, unpredictable behavior environments, it necessary consider computation issues challenging problem environment. However, best our knowledge, despite its importance, there not any systematic, comprehensive, detailed survey game theory (GT)‐based this article, we provide a systematic literature review GT‐based approaches environment form classical taxonomy recognize state‐of‐the‐art important topic open well. The proposed classified into four main fields: mechanisms, auction theory, evolutionary hybrid‐base mechanisms. Next, these classes compared with each according factors performance metrics, case studies, utilized techniques, evaluation tools, advantages disadvantages discussed, Finally, future uncovered or weakly covered research challenges discussed concluded.

Language: Английский

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Task scheduling and VM placement to resource allocation in Cloud computing: challenges and opportunities

Cluster Computing, Journal Year: 2023, Volume and Issue: 26(5), P. 3069 - 3087

Published: July 8, 2023

Language: Английский

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An efficient power-aware VM allocation mechanism in cloud data centers: a micro genetic-based approach

Cluster Computing, Journal Year: 2020, Volume and Issue: 24(2), P. 919 - 934

Published: Aug. 9, 2020

Language: Английский

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A priority, power and traffic-aware virtual machine placement of IoT applications in cloud data centers

Journal of Systems Architecture, Journal Year: 2021, Volume and Issue: 115, P. 101996 - 101996

Published: Jan. 14, 2021

Language: Английский

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Deep reinforcement learning for multi-objective placement of virtual machines in cloud datacenters

Soft Computing, Journal Year: 2020, Volume and Issue: 25(19), P. 12569 - 12588

Published: Dec. 12, 2020

Abstract The ubiquitous diffusion of cloud computing requires suitable management policies to face the workload while guaranteeing quality constraints and mitigating costs. typical trade-off is between used power adherence a service-level metric subscribed by customers. To this aim, possible idea use an optimization-based placement mechanism select servers where deploy virtual machines. Unfortunately, high packing factors could lead performance security issues, e.g., machines can compete for hardware resources or collude leak data. Therefore, we introduce multi-objective approach compute optimal strategies considering different goals, such as impact outages, required datacenter, perceived users. Placement are found using deep reinforcement learning framework best heuristic each machine composing workload. Results indicate that our method outperforms bin heuristics widely in literature when either synthetic real workloads.

Language: Английский

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Virtual machine placement in cloud data centers using a hybrid multi-verse optimization algorithm

Artificial Intelligence Review, Journal Year: 2020, Volume and Issue: 54(3), P. 2221 - 2257

Published: Sept. 27, 2020

Language: Английский

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Decomposition-based multi-objective evolutionary algorithm for virtual machine and task joint scheduling of cloud computing in data space

Swarm and Evolutionary Computation, Journal Year: 2023, Volume and Issue: 77, P. 101230 - 101230

Published: Jan. 12, 2023

Language: Английский

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Power efficient virtual machine placement in cloud data centers with a discrete and chaotic hybrid optimization algorithm

Cluster Computing, Journal Year: 2020, Volume and Issue: 24(2), P. 1293 - 1315

Published: Sept. 28, 2020

Language: Английский

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