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SCIENCE CHINA Information Sciences, Volume 59, Issue 2: 022310(2016) https://doi.org/10.1007/s11432-015-5378-7

Virtual network embedding for hybrid cloud rendering in optical and data center networks

Weigang HOU1,2,3, Lei GUO1,*
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  • ReceivedFeb 13, 2015
  • AcceptedMar 30, 2015
  • PublishedJan 5, 2016

Abstract

Animation rendering consumes massive computation time, therefore cloud rendering is emerging as a solution. Cloud rendering runs over the Data Center Network (DCN) and consolidates heterogeneous resources into a single cloud renderfarm, where plentiful computing resources can sufficiently accelerate any rendering process. And if one user wants to get a quick animation result, a high-speed optical interconnection is an urgent requirement, thus cloud rendering needs a convergence of Optical and DCN (ODCN) as the substrate network. In the ODCN supporting cloud rendering, each rendering task will be successfully handled only when we embed its virtual network into the cloud renderfarm. But because a virtual network includes virtual machines and virtual lightpaths, we must simultaneously perform the node-level mapping between virtual machine and server, as well as link-level mapping between virtual lightpath and fiber link(s). In addition, the joint implementation of the Photorealistic cloud Rendering (PR) and Non-Photorealistic cloud Rendering (NPR) should be considered to exhibit the unique animation effect with the low mapping cost. In this paper, considering the unique characteristic of hybrid cloud rendering, we flexibly select routing strategies according to the rendering task type. We then utilize server consolidation and traffic grooming to achieve node- and link-level mappings, respectively, thus building a mapping-cost-aware cloud renderfarm that includes multiple virtual networks. The mathematical formulation is also made with a bound analysis. Especially for the lower bound, we analyze the least number of servers and wavelengths (i.e., mapping cost) consumed by hybrid cloud rendering. In terms of heuristics, according to the processing order of rendering tasks, Smaller Virtual Resource First (SVRF) and Manycast Routing First (MRF) algorithms are proposed by us. In SVRF, NPR tasks are first tackled and then PR tasks follow. MRF is a reverse process of SVRF. The simulation results demonstrate the effectiveness of our methods in reducing the mapping cost because the heuristic solution well matches the lower bound.


References

[1] Assawamekin N, Kijsipongse E. Design and implementation of bit torrent file system for distributed animation rendering. In: Proceedings of IEEE International Computer Science and Engineering Conference, Nakorn Pathom, 2013. 68--72. Google Scholar

[2] Carroll D M, Hadzic I, Katsak A W. Bell Labs Tech J, 2012, 17: 55-66 CrossRef Google Scholar

[3] Hu X Y, Sun B, Liang X H, et al. An improved cloud rendering method. In: Proceedings of IEEE International Conference on Image and Graphics, Xi'an, 2009. 853--858. Google Scholar

[4] Georgakilas K N, Tzanakaki A, Anastasopoulos M, et al. IEEE/OSA J Opt Commun Netw, 2012, 4: 681-691 CrossRef Google Scholar

[5] Anastasopoulos M, Georgakilas K, Tzanakaki A. Evolutionary optimization for energy efficient service provisioning in IT and optical network infrastructures. In: Proceedings of IEEE European Conference and Exhibition on Optical Communication, Geneva, 2011. 1--3. Google Scholar

[6] Anastasopoulos M P, Tzanakaki A. Adaptive virtual infrastructure planning over interconnected IT and optical network resources using evolutionary game theory. In: Proceedings of IEEE International Conference on Optical Network Design and Modeling, Colchester, 2012. 1--5. Google Scholar

[7] Anastasopoulos M P, Tzanakaki A, Georgakilas K. Virtual infrastructure planning in elastic cloud deploying optical networking. In: Proceedings of IEEE International Conference on Cloud Computing Technology and Science, Athens, 2011. 685--689. Google Scholar

[8] Tzanakaki A, Anastasopoulos M P, Georgakilas K, et al. Energy aware planning of multiple virtual infrastructures over converged optical network and IT physical resources. In: Proceedings of IEEE European Conference and Exhibition on Optical Communication, Geneva, 2011. 1--3. Google Scholar

[9] Hou W G, Guo L, Liu Y J, et al. IEEE Netw, 2013, 27: 52-58 Google Scholar

[10] Kantarci B, Mouftah H T. Energy-efficient cloud services over wavelength-routed optical transport networks. In: Proceedings of IEEE Global Telecommunications Conference, Houston, 2011. 1--5. Google Scholar

[11] Speitkamp B, Bichler M. IEEE Trans Serv Comput, 2010, 3: 266-278 CrossRef Google Scholar

[12] Shen G, Tucker R S. IEEE/OSA J Opt Commun Netw, 2009, 1: 176-186 CrossRef Google Scholar

[13] Sun J, Wang Z W, Chen Z, et al. Sci China Inf Sci, 2013, 56: 032114-186 Google Scholar

[14] Du S, Zhang S F, Peng Y F, et al. Sci China Inf Sci, 2013, 56: 042306-186 Google Scholar

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