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Adaptive Allocation of Multi-class Tasks in the Cloud

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Computer and Information Sciences (ISCIS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 935))

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Abstract

Cloud computing enables the accommodation of an increasing number of applications in shared infrastructures. The routing for the incoming jobs in the cloud has become a real challenge due to the heterogeneity in both workload and machine hardware and the changes of load conditions over time. The present paper design and investigate the adaptive dynamic allocation algorithms that take decisions based on on-line and up-to-date measurements, and make fast online decisions to achieve both desirable QoS levels and high resource utilization. The Task allocation platform (TAP) is implemented as a practical system to accommodate the allocation algorithms and perform online measurement. The paper studies the potential of our proposed algorithms to deal with multi-class tasks in heterogeneous cloud environments and the experimental evaluations are also presented.

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Authors and Affiliations

  1. Imperial College London, London, UK

    Lan Wang

Authors
  1. Lan Wang
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Correspondence to Lan Wang .

Editor information

Editors and Affiliations

  1. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland

    Tadeusz Czachórski

  2. Department of Electrical and Electronic Engineering, Imperial College London, London, UK

    Erol Gelenbe

  3. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland

    Krzysztof Grochla

  4. University of Houston, Houston, TX, USA

    Ricardo Lent

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Wang, L. (2018). Adaptive Allocation of Multi-class Tasks in the Cloud. In: Czachórski, T., Gelenbe, E., Grochla, K., Lent, R. (eds) Computer and Information Sciences. ISCIS 2018. Communications in Computer and Information Science, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-00840-6_2

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  • DOI: https://doi.org/10.1007/978-3-030-00840-6_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00839-0

  • Online ISBN: 978-3-030-00840-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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