scispace - formally typeset
Journal ArticleDOI

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

Reads0
Chats0
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
More filters
Journal ArticleDOI

Fault tolerance and QoS scheduling using CAN in mobile social cloud computing

TL;DR: Fault tolerance and QoS scheduling using CAN as the underlying MSCC to logically manage the locations of mobile devices is proposed and results show that the proposed scheduling algorithm enhances cloud service execution time, finish time and reliability and reduces the cloud service error rate.
Proceedings ArticleDOI

Optimizing the Energy Efficiency of Message Exchanging for Service Distribution in Interoperable Infrastructures

TL;DR: A total decentralized nodes topology in which message exchanging algorithm allows dissemination of communication messages within a decoupled node formation setting in which obtainable resources are ranked and hierarchically categorized based on the performance criterion e.g. latency competency.
Journal ArticleDOI

A sequential pattern mining model for application workload prediction in cloud environment

TL;DR: A novel Prediction mOdel based on SequentIal paTtern mINinG (POSITING) that considers correlation between different resources and extracts behavioural patterns of applications independently of the fixed pattern length explicitly is proposed.
Proceedings ArticleDOI

A Cooperative Two-Tier Energy-Aware Scheduling for Real-Time Tasks in Computing Clouds

TL;DR: A cooperative two-tier task scheduling approach that regulates the execution speeds of real-time tasks in a way that a host reaches the optimum level of utilization instead of migrating its tasks to other hosts is proposed.
Journal ArticleDOI

Cost-efficient coordinated scheduling for leasing cloud resources on hybrid workloads

TL;DR: A coordinated scheduling algorithm that uses a priority function to handle interactive services, meet stringent service response time, and in the same time collect residual resources needed for batch jobs to solve the problem of overproduce virtual-machine (VM) instances for interactive services.
References
More filters
Journal ArticleDOI

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.
Related Papers (5)