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

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.

Tackling uncertainty in long-term predictions for host overload and underload detection in cloud computing

“…To conduct controllable and repeatable experiments in a large cloud infrastructure, the CloudSim [9] simulator is used. It is a well known simulator that permits the simulation of dynamic VM resource allocation and energy consumption in virtualized environments.…”

“…Experimental evaluations based on the CloudSim [9] simulator and PlanetLab [10] workloads show that the proposed approach achieves better performance and stability compared to the other approaches.…”

A Study on Simulation Tools in Cloud Computing

“…CloudSim: CloudSim [6] is an outstanding cloud computing test system based upon GridSim. It has been created in the CLOUDS Laboratory at the University of Melborne.…”

A Load Balancing Analysis of Cloud Base Application with different Service Broker Policies

“…The preempted process is then placed at the back of the ready list [11] [12]. Load balancing is a methodology to distribute workload across multiple computers, or other resources over the network links [10]. Load balancing achieves optimal resource utilization, maximize throughput.…”

“…To support the infrastructure and applicationlevel requirements on-demand virtualization enabled resources, simulators are required. Few simulators like CloudSim [10] and CloudAnalyst [4][9] are available. CloudAnalyst has been used in this paper as a simulation tool.…”