GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing
Rajkumar Buyya,Manzur Murshed +1 more
Reads0
Chats0
TLDR
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.Abstract:
SUMMARY Clusters, Grids, and peer-to-peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing. They enable aggregation of distributed resources for solving largescale problems in science, engineering, and commerce. In Grid and P2P computing environments, the resources are usually geographically distributed in multiple administrative domains, managed and owned by different organizations with different policies, and interconnected by wide-area networks or the Internet. This 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. The resource management and scheduling systems for Grid computing need to manage resources and application execution depending on either resource consumers’ or owners’ requirements, and continuously adapt to changes in resource availability. The management of resources and scheduling of applications in such large-scale distributed systems is a complex undertaking. In order to prove the effectiveness of resource brokers and associated scheduling algorithms, their performance needs to be evaluated under different scenarios such as varying number of resources and users with different requirements. In a Grid environment, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. To overcome this limitation, we have developed a Java-based discrete-event Grid simulation toolkit called GridSim. The toolkit supports modeling and simulation of heterogeneous Grid resources (both time- and space-shared), users and application models. It provides primitives for creation of application tasks, mapping of tasks to resources, and their management. To demonstrate suitability of the GridSim toolkit, we have simulated a Nimrod-Gread more
Citations
More filters
Journal ArticleDOI
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
TL;DR: 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.
Posted Content
Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and Opportunities
TL;DR: This paper proposes CloudSim: an extensible simulation toolkit that enables modelling and simulation of Cloud computing environments and allows simulation of multiple Data Centers to enable a study on federation and associated policies for migration of VMs for reliability and automatic scaling of applications.
Proceedings ArticleDOI
Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities
TL;DR: CloudSim as mentioned in this paper is an extensible simulation toolkit that enables modelling and simulation of cloud computing environments, and it supports the creation of one or more virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to suitable VMs.
Proceedings ArticleDOI
The cost of doing science on the cloud: the Montage example
TL;DR: Using the Amazon cloud fee structure and a real-life astronomy application, the cost performance tradeoffs of different execution and resource provisioning plans are studied and it is shown that by provisioning the right amount of storage and compute resources, cost can be significantly reduced with no significant impact on application performance.
Proceedings ArticleDOI
CloudAnalyst: A CloudSim-Based Visual Modeller for Analysing Cloud Computing Environments and Applications
TL;DR: CloudAnalyst is developed to simulate large-scale Cloud applications with the purpose of studying the behavior of such applications under various deployment configurations and helps developers with insights in how to distribute applications among Cloud infrastructures and value added services such as optimization of applications performance and providers incoming with the use of Service Brokers.
References
More filters
Journal ArticleDOI
Globus: a Metacomputing Infrastructure Toolkit
Ian Foster,Carl Kesselman +1 more
TL;DR: The Globus system is intended to achieve a vertically integrated treatment of application, middleware, and net work, an integrated set of higher level services that enable applications to adapt to heteroge neous and dynamically changing metacomputing environ ments.
The omnet++ discrete event simulation system
TL;DR: OMNeT++ is fully programmable and modular, and it was designed from the ground up to support modeling very large networks built from reusable model components.
Book
Peer-to-Peer: Harnessing the Power of Disruptive Technologies
TL;DR: Key peer-to-peer pioneers take us beyond the headlines and hype and show how the technology is changing the way the authors communicate and exchange information.
Proceedings ArticleDOI
Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid
TL;DR: The proposed Nimrod/G grid-enabled resource management and scheduling system builds on the earlier work on Nimrod and follows a modular and component-based architecture enabling extensibility, portability, ease of development, and interoperability of independently developed components.
Journal ArticleDOI
Economic models for resource management and scheduling in Grid computing
TL;DR: A computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments is proposed and some of the economic models in resource trading and scheduling are demonstrated using the Nimrod/G resource broker.