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 q 2010 John Wiley & Sons, Ltd.
Received 3 November 2009; Revised 4 June 2010; Accepted 14 June 2010
KEY WORDS: Cloud computing; modelling and simulation; performance evaluation; resource management;
application scheduling
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 q 2010 John Wiley & Sons, Ltd.
Received 3 November 2009; Revised 4 June 2010; Accepted 14 June 2010
KEY WORDS: Cloud computing; modelling and simulation; performance evaluation; resource management;
application scheduling
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