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Revenue Creation for Rate Adaptive Stream Management in Multi-tenancy Environments

  • José Ángel Bañares
  • Omer F. Rana
  • Rafael Tolosana-Calasanz
  • Congduc Pham
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8193)

Abstract

With the increasing availability of streaming applications from mobile devices to dedicated sensors, understanding how such streaming content can be processed within some time threshold remains an important requirement. We investigate how a computational infrastructure responds to such streaming content based on the revenue per stream – taking account of the price paid to process each stream, the penalty per stream if the pre-agreed throughput rate is not met, and the cost of resource provisioning within the infrastructure. We use a token-bucket based rate adaptation strategy to limit the data injection rate of each data stream, along with the use of a shared token-bucket to enable better allocation of computational resource to each stream. We demonstrate how the shared token-bucket based approach can enhance the performance of a particular class of applications, whilst still maintaining a minimal quality of service for all streams entering the system.

Keywords

Data Stream Rule Engine Token Bucket Unused Resource Gold User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • José Ángel Bañares
    • 2
  • Omer F. Rana
    • 1
  • Rafael Tolosana-Calasanz
    • 2
  • Congduc Pham
    • 3
  1. 1.School of Computer Science & InformaticsCardiff UniversityUnited Kingdom
  2. 2.Dpto. de Informática e Ingeniería de SistemasUniversidad de ZaragozaSpain
  3. 3.LIUPPA LaboratoryUniversity of PauFrance

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