Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities

By Rajkumar Buyya, R. Ranjan, Rodrigo Neves Calheiros. International Symposium on High Performance Computing Systems and Applications, 2009

1,257 citations recorded by the source corpus.

Cloud computing aims to power the next generation data centers and enables application service providers to lease data center capabilities for deploying applications depending on user QoS (Quality of Service) requirements. Cloud applications have different composition, configuration, and deployment requirements. Quantifying the performance of resource allocation policies and application scheduling algorithms at finer details in Cloud computing environments for different application and service models under varying load, energy performance (power consumption, heat dissipation), and system size is a challenging problem to tackle. To simplify this process, in this paper we propose CloudSim: an extensible simulation toolkit that enables modelling and simulation of Cloud computing environments. The CloudSim toolkit supports modelling and creation of one or more virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to suitable VMs. It also 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.

Subfields: General Health Professions, Philosophy

View Paper: https://www.semanticscholar.org/paper/11e4e71b13860045fa9abff5ea227463d0e7562b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Health Professions

1. Anton Beloglazov
2. Rajkumar Buyya
3. Mohit Taneja
4. Alan Davy
5. Jemal H. Abawajy
6. Rodrigo Neves Calheiros

In Philosophy

1. Anton Beloglazov
2. Rajkumar Buyya
3. Mohit Taneja
4. Alan Davy
5. Jemal H. Abawajy
6. Rodrigo Neves Calheiros

Citations in the corpus

• A critical review of cloud computing: researching desires and realities (2012, background): “This is the desire that the cloud provider must endeavour to guarantee security, availability and response time which are at least equivalent in quality to that experienced by a locally running client-server service on a local area network (Buyya et al ., 2009a; Brynjolfsson et al ., 2010).”
• Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges (2010, methodology): “Current state-of-the-art Cloud infrastructure such as Amazon EC2 [12] neither support energy-efficient resource allocation that considers consumer preference for energy saving schemes, nor utilise sophisticated economic models to set the right incentives for consumers to reveal information about…”
• CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms (2011, methodology): “This paper is a substantially extended version of a keynote paper [15], and it focuses on CloudSim.”
• GreenCloud: a packet-level simulator of energy-aware cloud computing data centers (2010, background): “Unlike the (only) existing cloud computing simulator CloudSim [8], GreenCloud extracts, aggregates, and makes information about the energy consumed by computing and communication elements of the data center available on an unprecedented fashion.”
• iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator (2012, methodology): “In the case of CloudSim [4], several research articles have been published with results obtained by using it [2, 5, 6, 15].”
• Cloud Task Scheduling Based on Load Balancing Ant Colony Optimization (2011, methodology): “Parameters Setting of the basic ACO and LBACO The performance evaluation of our proposed LBACO algorithm and the comparison study with other algorithms for task scheduling have been implemented on the CloudSim platform[13, 14], the CloudSim is developed to support simulation of heterogeneous cloud r”
• Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey (2014, background): “A cloud is defined as a place over network infrastructure where information technology (IT) and computing resources such as computer hardware, operating systems, networks, storage, databases, and even entire software applications are available instantly, on-demand as given in Buyya and Ranjan (2011)”
• Cloud task scheduling based on ant colony optimization (2013, background): “Simulation is a technique where a program models the behavior of the system (CPU, network etc.) by calculating the interaction between its different entities using mathematical formulas, or actually capturing and playing back observations from a production system [22].”
• CloudAnalyst: A CloudSim-Based Visual Modeller for Analysing Cloud Computing Environments and Applications (2010, background): “On the other side there are large-scale software systems providers, which develop applications such as social networking sites and e-commerce, which are gaining popularity on the Internet.”
• Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm (2017, methodology): “The application was formulated, modeled and deployed by building upon the components of iFogSim : a toolkit developed by Gupta et. al [19] over the CloudSim [20] framework for modeling and simulating IoT, Edge and Fog Computing environments.”
• The role of ICT and innovation in enhancing organizational performance: The catalysing effect of corporate entrepreneurship (2017, background): “The model will further help ICT managers and decision makers to consider the various challenges and opportunities posed by the new computing models, including wireless and mobile computing, cloud computing, and social media (Buyya, Ranjan, & Calheiros, 2009).”