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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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Proceedings ArticleDOI

EdgeCloudSim: An environment for performance evaluation of Edge Computing systems

TL;DR: A new simulator tool called EdgeCloudSim streamlined for Edge Computing scenarios is proposed, which builds upon CloudSim to address the specific demands of Edge Computing research and support necessary functionality in terms of computation and networking abilities.
Journal ArticleDOI

Workflow Scheduling in Multi-Tenant Cloud Computing Environments

TL;DR: A novel cloud-based workflow scheduling (CWSA) policy for compute-intensive workflow applications in multi-tenant cloud computing environments, which helps minimize the overall workflow completion time, tardiness, cost of execution of the workflows, and utilize idle resources of cloud effectively is proposed.
Proceedings ArticleDOI

LiRCUP: Linear Regression Based CPU Usage Prediction Algorithm for Live Migration of Virtual Machines in Data Centers

TL;DR: Experimental results on the real workload traces from more than a thousand Planet Lab VMs show that the proposed technique can significantly reduce the energy consumption and SLA violation rates.
Proceedings ArticleDOI

MuSIC: Mobility-Aware Optimal Service Allocation in Mobile Cloud Computing

TL;DR: A novel framework to model mobile applications as a location-time workflows (LTW) of tasks, here user mobility patterns are translated to a mobile service usage patterns and an efficient heuristic algorithm called MuSIC is proposed that is able to perform well, and scale well to a large number of users while ensuring high application QoS.
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A review of edge computing reference architectures and a new global edge proposal

TL;DR: A proposal for a tiered architecture with a modular approach that allows to manage the complexity of solutions not only for Industry 4.0 environments but also for other scenarios such as smart cities, smart energy, healthcare or precision agrotechnology.
References
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A view of cloud computing

TL;DR: The clouds are clearing the clouds away from the true potential and obstacles posed by this computing capability.
Book

The Grid 2: Blueprint for a New Computing Infrastructure

TL;DR: The Globus Toolkit as discussed by the authors is a toolkit for high-throughput resource management for distributed supercomputing applications, focusing on real-time wide-distributed instrumentation systems.
Journal ArticleDOI

Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility

TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
Journal ArticleDOI

The GRID: Blueprint for a New Computing Infrastructure

TL;DR: The main purpose is to update the designers and users of parallel numerical algorithms with the latest research in the field and present the novel ideas, results and work in progress and advancing state-of-the-art techniques in the area of parallel and distributed computing for numerical and computational optimization problems in scientific and engineering application.
Journal ArticleDOI

GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing

TL;DR: This work states that clusters, Grids, and peer‐to‐peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing and introduces a number of resource management and application scheduling challenges in the domain of security, resource and policy heterogeneity, fault tolerance, continuously changing resource conditions, and politics.
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