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    Nutshell - Simulation Toolkit for Modeling Data Center Networks and Cloud Computing

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    Date
    2019
    Author
    Rahman, Ubaid Ur
    Bilal, Kashif
    Erbad, Aiman
    Khalid, Osman
    Khan, Samee U.
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    Abstract
    Cloud computing provides flexibility, reliability, and scalability to its consumers. Applications that run on Cloud are now more resource hungry than ever, and the need is constantly growing. The number of Cloud applications with diverse nature is growing, expecting greater performance in low cost. Fulfilling the quality of service (QoS) demands of such diverse applications is a challenging task and requires efficient network architectures, robust scheduling schemes, powerful and adaptable routing algorithms, reliable resource management, effective data exchange policies, and QoS improvement policies. Research community endeavors to provide solutions to various challenges faced by Cloud computing. These solutions must be tested thoroughly before their implementation in a real Cloud. Simulation seems a viable choice for testing a solution in different scenarios. There are a number of simulators available, focusing on certain aspects of Cloud while neglecting others. Their generalized implementation of the Cloud ignores various critical factors, such as networking characteristics, consequently affecting the tests and results of a solution. To tackle these issues, simplify simulation process, and provide the detailed implementation of the Cloud, we present Nutshell: a novel Cloud simulator that makes it easy to model, simulate, and experiment new Cloud solutions. Salient features offered by Nutshell include 1) provision of a platform for modeling and simulating Cloud infrastructure, 2) built-in essential components and helpers to create new architectures, 3) pre-built data center architectures, 4) plug-in-based architecture, 5) communication protocols, 6) pre-built virtual machine scheduler, 7) addressing schemes, 8) user applications, 9) virtual machines, 10) Job splitting, and 11) simulation data collection and exporting. - 2019 IEEE.
    DOI/handle
    http://dx.doi.org/10.1109/ACCESS.2019.2894725
    http://hdl.handle.net/10576/15628
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    • Computer Science & Engineering [‎2429‎ items ]

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