KeywordCloud computing; Virtualisation; Computational modelling; Hardware; Open source software; Organisations; Xen cloud platform; OpenNebula; CloudStack; OpenStack; Eucalyptus; AbiCloud; Nimbus; OpenIoT
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AbstractCloud computing is increasingly attracting large attention both in academic research and in industrial initiatives. However, despite the popularity, there is a lack of research on the suitability of software tools and parameters for creating and deploying Cloud test beds. Virtualization and how to set up virtual environments can be done through software tools, which are available as open source, but there still needs to be work in terms of which tools to use and how to monitor parameters with the suitability of hardware resources available. This paper discusses the concepts of virtualization, as a practical view point, presenting an in-depth critical analysis of open source cloud implementation tools such as CloudStack, Eucalyptus, Nimbus, OpenStack, OpenNebula, OpenIoT, to name a few. This paper analyzes the various toolkits, parameters of these tools, and their usability for researchers looking to deploy their own Cloud test beds. The paper also extends further in developing an experimental case study of using OpenStack to construct and deploy a test bed using current resources available in the labs at the University of Bradford. This paper contributes to the theme of software setups and open source issues for developing Cloud test bed for deploying and constructing private Cloud test bed.
CitationMohammed B and Kiran M (2015) Analysis of cloud testbeds using opensource solutions. In: Proceedings of the 3rd International Conference on Future Internet of Things and Cloud (FiCloud 2015). 24-26 Aug 2015, Rome, Italy: 195-203.
Link to publisher’s versionhttp://dx.doi.org/10.1109/FiCloud.2015.106
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A new Linux based TCP congestion control mechanism for long distance high bandwidth sustainable smart citiesMudassar, A.; Asri, N.M.; Usman, A.; Amjad, K.; Ghafir, Ibrahim; Arioua, M. (2018-02)People, systems, and things in the cities generate large amount of data which is considered to be the most scalable asset of any smart city. Linux users are rapidly increased in last few years, and many large multinational organizations are deploying long distance high bandwidth (LDHB) cloud networks for centralizing the data from various smart cities on a central location. TCP is responsible for reliable communication of data in these cloud networks. For reliability communication among various smart cities, a number of TCP congestion control mechanisms have been developed in the past. TCP Compound, TCP Fusion, and TCP CUBIC are the default TCP congestion control mechanisms for Microsoft Windows, Sun Solaris, and Linux operating systems respectively. The response function of TCP CUBIC is higher than the response function of Standard TCP, which is a trademark congestion control mechanism. As a result, TCP CUBIC does not behave friendly with Standard TCP in LDHB cloud networks. The Congestion Window (cwnd) reduction and growth of TCP CUBIC is very aggressive, which causes high packet loss rate and unfair share of available link bandwidth among competing flows from various smart cities. The aim of this research is to design a new TCP congestion control mechanism for Linux operating system to achieve maximum performance in LDHB cloud networks being used by smart cities. In this paper, congestion control module for slow start (CCM-SS) is designed by increasing the lower boundary limit of cwnd size in slow start phase of communication. Congestion control module for loss event (CCM-LE) is designed by increasing the cwnd reduction rate at each packet loss event and finally Advance Response Function for TCP CUBIC (ARFC) is proposed to design a new congestion control mechanism for Linux operating system. NS-2 is used to compare the performance of TCP CUBIC* with TCP CUBIC in short distance high bandwidth (SDHB) and long distance high bandwidth (LDHB) cloud networks. Results show that TCP CUBIC* has outperformed in LDHB networks, at least by a factor of 18% as compared to TCP CUBIC.
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Failure Analysis Modelling in an Infrastructure as a Service (Iaas) EnvironmentMohammed, Bashir; Modu, Babagana; Maiyama, Kabiru M.; Ugail, Hassan; Awan, Irfan U.; Kiran, Mariam (2018)Failure Prediction has long known to be a challenging problem. With the evolving trend of technology and growing complexity of high-performance cloud data centre infrastructure, focusing on failure becomes very vital particularly when designing systems for the next generation. The traditional runtime fault-tolerance (FT) techniques such as data replication and periodic check-pointing are not very effective to handle the current state of the art emerging computing systems. This has necessitated the urgent need for a robust system with an in-depth understanding of system and component failures as well as the ability to predict accurate potential future system failures. In this paper, we studied data in-production-faults recorded within a five years period from the National Energy Research Scientific computing centre (NERSC). Using the data collected from the Computer Failure Data Repository (CFDR), we developed an effective failure prediction model focusing on high-performance cloud data centre infrastructure. Using the Auto-Regressive Moving Average (ARMA), our model was able to predict potential future failures in the system. Our results also show a failure prediction accuracy of 95%, which is good.