GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing

By Rajkumar Buyya, Manzur Murshed. Concurrency and Computation, 2002

1,737 citations recorded by the source corpus.

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 large‐scale 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.

Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/c80d681c6136d2143485506dd83a37e40090c9eb

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Citations in the corpus

Cost-based scheduling of scientific workflow applications on utility grids (2005, methodology): “We use GridSim [ 7 ][20] to simulate a Grid testbed for our experiments.”
iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator (2012, methodology): “So, a new layer on top of GridSim was implemented to add the ability to simulate clouds.”
Economic-based Distributed Resource Management and Scheduling for Grid Computing (2002, methodology): “MOSIX [147], JaWS [127], Xenoservers [23], D’Agents [55], Rexec/Anemone [8], Mojo Nation [84], Mariposa [83], Mungi[33], Stanford Peers [10], G-Commerce [120], OCEAN [76], Nimrod-G [100], and GridSim [95]. These systems have been targeted to manage single or multiple resources for application domain”
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms (2011, methodology): “On the other hand, GridSim is an event-driven simulation toolkit for heterogeneous Grid resources.”
Grid'5000: a large scale and highly reconfigurable grid experimental testbed (2005, background): “GridSim [5] is a higher-level simulator, designed to investigate interactions and interferences between scheduling decisions taken by distributed brokers.”
The Grid Economy (2005, methodology): “…computing, They include Spawn [10], Popcorn [48], Java Market [72], Enhanced MOSIX [73], JaWS [66], Xenoservers [14], D'Agents [28], Rexec/Anemone [6], Mojo Nation [45], Mariposa [44], Mungi [18], Stanford Peers [8], G-Commerce [62], OCEAN [39], Nimrod-G [52], and GridSim [49], and Gridbus [57].”
Scheduling distributed applications: the SimGrid simulation framework (2003, background): “Note that the GridSim [ 4 ] project is very related to our work in scope and intent.”
NetworkCloudSim: Modelling Parallel Applications in Cloud Simulations (2011, neutral): “To support the research and development of Grid middleware, several simulators such as SimGrid [6] and GridSim [7] have been proposed.”
The Grid Workloads Archive (2008, background): “, GridSim [63], SimGrid [64], GangSim [65], and DGSim [31].”
The cost of doing science on the cloud: The Montage example (2008, methodology): “The simulations were done using the GridSim toolkit [13].”
Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities (2009, methodology): “On the other hand, GridSim is an event-driven simulation toolkit for heterogeneous Grid resources.”
Versatile, scalable, and accurate simulation of distributed applications and platforms (2014, neutral): “This is the case for the GridSim [15] grid simulator and its follow-up cloud computing simulator, CloudSim [16].”
CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services (2009, methodology): “On the other hand, GridSim is an event-driven simulation toolkit for heterogeneous Grid resources.”
Power Aware Scheduling of Bag-of-Tasks Applications with Deadline Constraints on DVS-enabled Clusters (2007, methodology): “In this section, we present simulation results of the proposed DVS-based cluster scheduling algorithms using the GridSim toolkit [26, 27].”
CloudAnalyst: A CloudSim-Based Visual Modeller for Analysing Cloud Computing Environments and Applications (2010, background): “If requests are received causing this threshold to be exceeded in all available virtual machines, then the requests are queued until a virtual machine becomes available.”
Grids and Grid technologies for wide‐area distributed computing (2002, methodology): “GridSim [32] is a toolkit for modeling and simulation of Grid resources and application scheduling.”
SimGrid: A Generic Framework for Large-Scale Distributed Experiments (2008, background): “The inordinate level of accuracy of fine grain d.e.s. may hinder performance (c.f. §4).”
Identity-Based Authentication for Cloud Computing (2009, methodology): “Simulation Platform and Reference The platform of simulation experiment is GridSim [16] which is a simulation platform based on Java.”