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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

An EDA-GA Hybrid Algorithm for Multi-Objective Task Scheduling in Cloud Computing

TL;DR: An EDA-GA hybrid scheduling algorithm based on EDA (estimation of distribution algorithm) and GA (genetic algorithm) that can effectively reduce the task completion time and improve the load balancing ability is developed.
Proceedings ArticleDOI

An ACO-based Scheduling Strategy on Load Balancing in Cloud Computing Environment

TL;DR: Experimental results show that ACO-VMM outperforms the existing migration strategies by achieving load balance of whole system, as well as reducing the number of migrations and maintaining the required performance levels.
Journal ArticleDOI

Highly-cited papers in software engineering: The top 100

TL;DR: In this paper, the authors identify the papers in the area of software engineering that have influenced others the most as measured by citation count and identify and classify the top 100 highly-cited SE papers in terms of two metrics: total number of citations and average annual numbers of citations.
Journal ArticleDOI

An adaptive heuristic for managing energy consumption and overloaded hosts in a cloud data center

TL;DR: Adapt heuristic algorithms, namely least medial square regression for overloaded host detection and minimum utilization prediction for VM selection from overloaded hosts are proposed, reducing CDC energy consumption with minimal SLA.
Journal ArticleDOI

A workload clustering based resource provisioning mechanism using Biogeography based optimization technique in the cloud based systems

TL;DR: The proposed mechanism utilized biogeography-based optimization technique with K-means clustering to classify the cloud workloads according to their quality of service (QoS) requirements and used Bayesian learning technique to specify suitable resource provisioning actions to satisfy the QoS requirements of cloud-based applications.
References
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A view of cloud computing

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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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