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resource provisioning for computation and communication in multi-cell wireless networks

High Technology Letters 2021年第2期27卷 121-128页

作者： Yang Xiumei Chen Huaxia Zhang Mengying Shanghai Institute of Microsystem and Information Technology Chinese Academy of SciencesShanghai 200050P.R.China Key Laboratory of Wireless Sensor Network and Communications Chinese Academy of SciencesShanghai 200050P.R.China

The convergence of computation and communication at network edges plays a significant role in coping with computation-intensive and delay-critical *** the stage of network planning,the resource provisioning problem for edge nodes has to be investigated to provide prior information for future system *** work focuses on how to quantify the computation capabilities of access points at network edges when provisioning resources of computation and communication in multi-cell wireless *** problem is formulated as a discrete and non-convex minimization problem,where practical constraints including delay requirements,the inter-cell interference,and resource allocation strategies are *** iterative algorithm is also developed based on decomposition theory and fractional programming to solve this *** analysis shows that the necessary computation capability needed for certain delay guarantee depends on resource allocation strategies for delay-critical *** delay-tolerant tasks,it can be approximately estimated by a derived lower bound which ignores the scheduling *** efficiency of the proposed algorithm is demonstrated using numerical results.

关键词： resource provisioning computation and communication multi-cell wireless network network edge

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A Review of Dynamic resource Management in Cloud Computing Environments

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Computer Systems Science & Engineering 2021年第3期36卷 461-476页

作者： Mohammad Aldossary Department of Computer Science College of Arts and SciencePrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia

In a cloud environment, Virtual Machines (VMs) consolidation andresource provisioning are used to address the issues of workload *** consolidation aims to move the VMs from one host to another in order toreduce the number of active hosts and save power. Whereas resource provisioningattempts to provide additional resource capacity to the VMs as needed in order tomeet Quality of Service (QoS) requirements. However, these techniques have aset of limitations in terms of the additional costs related to migration and scalingtime, and energy overhead that need further consideration. Therefore, this paperpresents a comprehensive literature review on the subject of dynamic resourcemanagement (i.e., VMs consolidation and resource provisioning) in cloud computing environments, along with an overall discussion of the closely relatedworks. The outcomes of this research can be used to enhance the developmentof predictive resource management techniques, by considering the awareness ofperformance variation, energy consumption and cost to efficiently manage thecloud resources.

关键词： Cloud computing resource management VM consolidation live migration resource provisioning auto-scaling

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Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

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Intelligent Automation & Soft Computing 2023年第4期36卷 223-233页

作者： S.Sridevi Jeevaa Katiravan Department of Computer Science and Engineering Velammal Engineering CollegeChennai600066India

Scientiﬁc workﬂows have gained the emerging attention in sophisti-cated large-scale scientiﬁc problem-solving *** pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for executing scientiﬁc workﬂow *** the cloud is not a utopian environment,failures are inevitable that may result in experiencingﬂuctuations in the delivered *** a single task failure occurs in workﬂow based applications,due to its task dependency nature,the reliability of the overall system will be affected *** rather than reactive fault-tolerant approaches,proactive measures are vital in scientiﬁc workﬂ*** work puts forth an attempt to con-centrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm(IWDA)combined with an efﬁcient machine learning approach-Support Vector Regression(SVR)for task failure prognostica-tion which facilitates proactive fault-tolerance in the scheduling of scientiﬁc workﬂow *** failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workﬂ*** experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.

关键词： Failure prediction intelligent water drops support vector regression proactive fault-tolerance scientiﬁc workﬂows precision accuracy resource provisioning

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