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

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• 作者：Weigang Hou ; Lei Guo
• 关键词：hybrid cloud rendering ; optical and data center network ; virtual network embedding ; mapping cost ; lower bound ; 022310 ; 混合云渲染
光数据中心网络 虚拟网络嵌入 ; 映射成本 ; 下限值
• 刊名：SCIENCE CHINA Information Sciences
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：59
• 期：2
• 页码：1-14
• 全文大小：616 KB
• 参考文献：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
  2.Carroll D M, Hadzic I, Katsak A W. 3D rendering in the cloud. Bell Labs Tech J, 2012, 17: 55–66CrossRef
  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
  4.Georgakilas K N, Tzanakaki A, Anastasopoulos M, et al. Converged optical network and data center virtual infrastructure planning. IEEE/OSA J Opt Commun Netw, 2012, 4: 681–691CrossRef
  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
  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
  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
  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
  9.Hou W G, Guo L, Liu Y J, et al. Virtual network planning for converged optical and data centers: ideas and challenges. IEEE Netw, 2013, 27: 52–58CrossRef
  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
  11.Speitkamp B, Bichler M. A mathematical programming approach for server consolidation problems in virtualized data centers. IEEE Trans Serv Comput, 2010, 3: 266–278CrossRef
  12.Shen G, Tucker R S. Energy-minimized design for IP Over WDM networks. IEEE/OSA J Opt Commun Netw, 2009, 1: 176–186CrossRef
  13.Sun J, Wang ZW, Chen Z, et al. Parallel lightpath provisioning under wavelength continuity constraint in multi-domain optical networks based on hierarchical path computation element. Sci China Inf Sci, 2013, 56: 032114MathSciNet
  14.Du S, Zhang S F, Peng Y F, et al. Power-efficient RWA in dynamic WDM optical networks considering different connection holding times. Sci China Inf Sci, 2013, 56: 042306CrossRef MathSciNet
  
• 作者单位：Weigang Hou (1) (2) (3)
  Lei Guo (1)
  
  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China
  2. State Key Laboratory of Networking and Switching Technology, Beijing, 100876, China
  3. State Key Laboratory of Information Photonics and Optical Communications, Beijing, 100876, China
  
• 刊物类别：Computer Science
• 刊物主题：Chinese Library of Science
  Information Systems and Communication Service
  
• 出版者：Science China Press, co-published with Springer
• ISSN：1869-1919

文摘

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 DC 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. Keywords hybrid cloud rendering optical and data center network virtual network embedding mapping cost lower bound