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Journal ArticleDOI

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

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TLDR
The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.
Abstract
Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end-users under a usage-based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter-networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter-networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy-efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns. Copyright © 2010 John Wiley & Sons, Ltd.

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Journal ArticleDOI

Maximizing quality of experience through context-aware mobile application scheduling in cloudlet infrastructure

TL;DR: This paper presents the first work in this domain that inscribes the optimal scheduling problem for mobile application software execution requests with three‐dimensional context parameters, and demonstrates that the QCASH outperforms the state‐of‐the‐art works well across the success rate, waiting time, and QoE.
Proceedings ArticleDOI

Stream-based admission control and scheduling for video transcoding in cloud computing

TL;DR: In order to prevent transcoding jitters in the admitted streams, a job scheduling mechanism is introduced, which drops a small proportion of video frames from a video segment to ensure continued delivery of video contents to the user.
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SSLB: Self-Similarity-Based Load Balancing for Large-Scale Fog Computing

TL;DR: This work examines the runtime characteristics of fog infrastructure and proposes SSLB, a self-similarity-based load balancing mechanism for large-scale fog computing and proposes an adaptive threshold policy and corresponding scheduling algorithm, which successfully guarantees the efficiency of SSLB.
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The placement method of resources and applications based on request prediction in cloud data center

TL;DR: A reconfiguration framework based on a request prediction, which anticipates the application request volume in advance and can work out the allocation scheme which can improve the resource utilization ratio as well as lower energy consumption is put forward.
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A Multiqueue Interlacing Peak Scheduling Method Based on Tasks’ Classification in Cloud Computing

TL;DR: A scheduling method called interlacing peak that can balance loads and improve the effects of resource allocation and utilization effectively is proposed and shows advantage over other similar standard algorithms.
References
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