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CloudSim is a framework for modeling and simulation of cloud computing infrastructures and services. [1] Originally built primarily at the Cloud Computing and Distributed Systems (CLOUDS) Laboratory, [2] the University of Melbourne, Australia, CloudSim has become one of the most popular open source [citation needed] cloud simulators in the research and academia.
In computing, a scenario (UK: / s ɪ ˈ n ɑː r i oʊ /, US: / s ə ˈ n ɛər i oʊ /; loaned from Italian scenario (pronounced [ʃeˈnaːrjo]), from Latin scena 'scene' [1]) is a narrative of foreseeable interactions of user roles (known in the Unified Modeling Language as 'actors') and the technical system, which usually includes computer hardware and software.
"A cloud deployment model represents the way in which cloud computing can be organized based on the control and sharing of physical or virtual resources." [3] Cloud deployment models define the fundamental patterns of interaction between cloud customers and cloud providers. They do not detail implementation specifics or the configuration of ...
Platform as a service (PaaS) or application platform as a service (aPaaS) or platform-based service is a cloud computing service model where users provision, instantiate, run and manage a modular bundle of a computing platform and applications, without the complexity of building and maintaining the infrastructure associated with developing and launching application(s), and to allow developers ...
Cloud management is the management of cloud computing products and services. Public clouds are managed by public cloud service providers, which include the public cloud environment’s servers, storage, networking and data center operations. [1] Users may also opt to manage their public cloud services with a third-party cloud management tool.
OpenNebula is an open source cloud computing platform for managing heterogeneous data center, public cloud and edge computing infrastructure resources. OpenNebula manages on-premises and remote virtual infrastructure to build private, public, or hybrid implementations of infrastructure as a service (IaaS) and multi-tenant Kubernetes deployments.
Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...
[1] [2] Elasticity is a defining characteristic that differentiates cloud computing from previously proposed distributed computing paradigms, such as grid computing. The dynamic adaptation of capacity, e.g., by altering the use of computing resources, to meet a varying workload is called "elastic computing". [3] [4]