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Bandwidth on-demand for multimedia big data transfer across geo-distributed cloud data centers

Yassine, A ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1109/TCC.2016.2617369
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2020
  4. Abstract:
  5. Multimedia content is massively generated from various applications and devices, and processed in cloud data centers. Multimedia service providers prefer that their data are processed in data centers close to users in order to offer them high performance and reliable multimedia services that meet the requirements specified in the Service Level of Agreement (SLA). This requires transferring huge data sets of video streams, games content, images etc. across geographically distributed cloud data centers using underutilized bandwidth in backbone transport networks. As the amount of multimedia content increases, the demand to transfer big data sets across data centers increases as well. As such, the leftover bandwidth that appears at different times and for different durations in the backbone network becomes insufficient to satisfy the rapidly increasing demand for multimedia big data transfer. This challenge led to the creation of multi-rate Bandwidth on-Demand (BoD) service offerings for communication between geographically distributed cloud data centers. In this paper, we focus on BoD services which are offered by the Dense Wavelength Division Multiplexing (DWDM) layer because of its huge capacity. We propose a BoD broker which employs a scheduling algorithm that considers various deadlines of multimedia big data transfer requests. The broker in our model leverages the concept of standby wavelengths to minimize peak traffic and accommodate time requirements of delay-tolerant and delay-intolerant transfer requests. We also study strategies of routing and wavelength assignment using Mixed Integer Programming (MIP) optimization to rapidly handle volumes of multimedia big data transfer requests. © 2013 IEEE
  6. Keywords:
  7. Bandwidth on-demand ; Data centers ; Mixed integer programming ; Multimedia big data ; Scheduling ; Transport network ; Bandwidth ; Big data ; Data transfer ; Dense wavelength division multiplexing ; Integer programming ; Multimedia services ; Multimedia systems ; Bandwidth on demand ; Cloud data centers ; Distributed clouds ; Mixed integer programming (MIP) ; Multimedia contents ; Routing and wavelength assignment ; Time requirements ; Transport networks ; Data streams
  8. Source: IEEE Transactions on Cloud Computing ; Volume 8, Issue 4 , 2020 , Pages 1189-1198
  9. URL: https://ieeexplore.ieee.org/document/7590088