A multi-objective ant colony system algorithm for virtual machine placement in cloud computing

Journal of Computer and System Sciences, Год журнала: 2013, Номер 79(8), С. 1230 - 1242

Опубликована: Март 13, 2013

Язык: Английский

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Joint Optimization of Task Scheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System

IEEE Transactions on Computers, Год журнала: 2016, Номер 65(12), С. 3702 - 3712

Опубликована: Фев. 29, 2016

Traditional standalone embedded system is limited in their functionality, flexibility, and scalability. Fog computing platform, characterized by pushing the cloud services to network edge, a promising solution support strengthen traditional system. Resource management always critical issue performance. In this paper, we consider fog supported software-defined system, where task images lay storage server while computations can be conducted on either device or computation server. It significant design an efficient scheduling resource strategy with minimized completion time for promoting user experience. To end, three issues are investigated paper: 1) how balance workload client servers, i.e., scheduling, 2) place management, 3) I/O interrupt requests among servers. They jointly considered formulated as mixed-integer nonlinear programming problem. deal its high complexity, computation-efficient proposed based our formulation validated extensive simulation studies.

Язык: Английский

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An Energy Efficient Ant Colony System for Virtual Machine Placement in Cloud Computing

IEEE Transactions on Evolutionary Computation, Год журнала: 2016, Номер 22(1), С. 113 - 128

Опубликована: Ноя. 22, 2016

Virtual machine placement (VMP) and energy efficiency are significant topics in cloud computing research. In this paper, evolutionary is applied to VMP minimize the number of active physical servers, so as schedule underutilized servers save energy. Inspired by promising performance ant colony system (ACS) algorithm for combinatorial problems, an ACS-based approach developed achieve goal. Coupled with order exchange migration (OEM) local search techniques, resultant termed OEMACS. It effectively minimizes used assignment virtual machines (VMs) from a global optimization perspective through novel strategy pheromone deposition which guides artificial ants toward solutions that group candidate VMs together. The OEMACS variety problems differing VM sizes environments homogenous heterogeneous servers. results show generally outperforms conventional heuristic other evolutionary-based approaches, especially on bottleneck resource characteristics, offers savings more efficient use different resources.

Язык: Английский

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An overview of virtual machine placement schemes in cloud computing

Journal of Network and Computer Applications, Год журнала: 2016, Номер 66, С. 106 - 127

Опубликована: Янв. 29, 2016

Язык: Английский

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Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

ACM Computing Surveys, Год журнала: 2015, Номер 48(1), С. 1 - 34

Опубликована: Авг. 10, 2015

Data centers in public, private, and hybrid cloud settings make it possible to provision virtual machines (VMs) with unprecedented flexibility. However, purchasing, operating, maintaining the underlying physical resources incurs significant monetary costs environmental impact. Therefore, providers must optimize use of by a careful allocation VMs hosts, continuously balancing between conflicting requirements on performance operational costs. In recent years, several algorithms have been proposed for this important optimization problem. Unfortunately, approaches are hardly comparable because subtle differences used problem models. This article surveys formulations algorithms, highlighting their strengths limitations, pointing out areas that need further research.

Язык: Английский

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A Survey on the Placement of Virtual Resources and Virtual Network Functions

IEEE Communications Surveys & Tutorials, Год журнала: 2018, Номер 21(2), С. 1409 - 1434

Опубликована: Дек. 3, 2018

Cloud computing and network slicing are essential concepts of forthcoming 5G mobile systems. Network slices essentially chunks virtual connectivity resources, configured provisioned for particular services according to their characteristics requirements. The success cloud hinges on the efficient allocation resources (e.g., VCPU VMDISK) optimal placement virtualized functions (VNFs) composing slices. In this context, paper elaborates issues that may disrupt VNFs machines (VMs). This classifies existing solutions VM based nature, whether is dynamic or static, objectives, metrics. then proposes a classification VNF approaches, first, regarding general management VNFs, second, target type.

Язык: Английский

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Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers

IEEE Systems Journal, Год журнала: 2014, Номер 10(2), С. 507 - 519

Опубликована: Июль 15, 2014

Cloud computing has emerged as the leading paradigm for information technology businesses. provides a platform to manage and deliver services around world over Internet. have helped businesses utilize on demand with no upfront investments. The cloud sustained its growth, which led increase in size number of data centers. Data centers thousands devices are deployed back end provide services. Computing redundantly ensure 24/7 availability. However, many studies pointed out that consume large amount electricity, thus calling energy-efficiency measures. In this survey, we discuss research issues related conflicting requirements maximizing quality (QoSs) (availability, reliability, etc.) delivered by while minimizing energy consumption center resources. paper, present concept inception controller can consolidate resources minimal effect QoS requirements. We software- hardware-based techniques architectures such server, memory, network be manipulated achieve efficiency.

Язык: Английский

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Comparing VM-Placement Algorithms for On-Demand Clouds

Опубликована: Ноя. 1, 2011

Much recent research has been devoted to investigating algorithms for allocating virtual machines (VMs) physical (PMs) in infrastructure clouds. Many such address distinct problems, as initial placement, consolidation, or tradeoffs between honoring service-level agreements and constraining provider operating costs. Even where similar problems are addressed, each individual team evaluates proposed under conditions, using various techniques, often targeted a small collection of VMs PMs. In this paper, we describe an objective method that can be used compare VM-placement large clouds, covering tens thousands PMs hundreds VMs. We demonstrate our by comparing 18 VM placement on-demand inspired open-source code the online bin-packing literature.

Язык: Английский

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A Hybrid Genetic Algorithm for the Energy-Efficient Virtual Machine Placement Problem in Data Centers

Neural Processing Letters, Год журнала: 2014, Номер 41(2), С. 211 - 221

Опубликована: Янв. 17, 2014

Язык: Английский

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Resource provision algorithms in cloud computing: A survey

Journal of Network and Computer Applications, Год журнала: 2016, Номер 64, С. 23 - 42

Опубликована: Фев. 7, 2016

Язык: Английский

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