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.read more
Citations
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Journal ArticleDOI
DynamicCloudSim: Simulating heterogeneity in computational clouds
TL;DR: This work presents DynamicCloudSim, which extends the popular simulation toolkit CloudSim with several factors of instability, including inhomogeneity and dynamic changes of performance at runtime as well as failures during task execution, to simulate the impact of instability on scientific workflow scheduling.
Proceedings ArticleDOI
Scheduling of fog networks with optimized knapsack by symbiotic organisms search
Dadmehr Rahbari,Mohsen Nickray +1 more
TL;DR: A knapsack-based scheduling optimized by symbiotic organisms search that is simulated in iFogsim as a standard simulator for fog computing and shows improvements in the energy consumption, total network usage, execution cost, and sensor lifetime.
Journal ArticleDOI
Securing Multimedia by Using DNA-Based Encryption in the Cloud Computing Environment
TL;DR: A novel DNA-based encryption scheme is proposed in this article for protecting multimedia files in the cloud computing environment and the efficiency of the proposed scheme over some well-known existing schemes is shown.
Proceedings ArticleDOI
Community Resources for Enabling Research in Distributed Scientific Workflows
TL;DR: This paper describes how a collection of tools and data that have enabled research in new techniques, algorithms, and systems for scientific workflows are used to investigate new techniques for efficient and robust workflow execution, as well as to provide improvements to the Pegasus Workflow Management System or other workflow tools.
Posted Content
A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing
Wanneng Shu,Wei Wang,Yunji Wang +2 more
TL;DR: In this article, the authors proposed an improved clonal selection algorithm based on time cost and energy consumption models in cloud computing environment, and analyzed the performance of their approach using the CloudSim toolkit.
References
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A view of cloud computing
Michael Armbrust,Armando Fox,Rean Griffith,Anthony D. Joseph,Randy H. Katz,Andy Konwinski,Gunho Lee,David A. Patterson,Ariel Rabkin,Ion Stoica,Matei Zaharia +10 more
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The Grid 2: Blueprint for a New Computing Infrastructure
Ian Foster,Carl Kesselman +1 more
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.
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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
Rajkumar Buyya,Manzur Murshed +1 more
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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