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Solution for Virtual Network Embedding Problem based on Simulated Annealing Genetic Algorithm

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Jianjun YU

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yjj691121: 金币+5, ★★★★★最佳答案, 谢谢 2012-10-25 09:20:41

Accession number:  20122415104335

  Title:  Solution for virtual network embedding problem based on simulated annealing genetic algorithm
  Authors:  Yu, Jianjun1
  Author affiliation:  1 Faculty of Information Engineering, Quzhou College of Technology, Quzhou, China
  Corresponding author:  Yu, J. (yjj691121@126.com)
  Source title:  2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings
  Abbreviated source title:  Int. Conf. Consum. Electron., Commun. Networks, CECNet - Proc.
  Monograph title:  2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings
  Issue date:  2012
  Publication year:  2012
  Pages:  579-582
  Article number:  6201795
  Language:  Chinese
  ISBN-13:  9781457714153
  Document type:  Conference article (CA)
  Conference name:  2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012
  Conference date:  April 21, 2012 - April 23, 2012
  Conference location:  Three Gorges, China
  Conference code:  90025
  Sponsor:  IEEE
  Publisher:  IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
  Abstract:  Assigning the resources of a virtual network to the components of a physical network, called Virtual Network Mapping, plays a central role in network virtualization. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms which had clear separation between the node mapping and the link mapping phases. In this paper we propose a Simulated Annealing genetic algorithm to optimize node mapping, and the heuristic algorithm or multi-commodity flow algorithms to solve the link mapping. Our experimental evaluations show that the proposed algorithm increases the acceptance ratio and the revenue while decreasing the cost incurred by the substrate network in the long run. © 2012 IEEE.
  Number of references:  15
  Main heading:  Simulated annealing
  Controlled terms:  Consumer electronics  -  Distributed computer systems  -  Genetic algorithms  -  Heuristic algorithms  -  Mapping
  Uncontrolled terms:  Acceptance ratio  -  Annealing genetic algorithm  -  Embedding problems  -  Experimental evaluation  -  Multi-commodity flow  -  Network virtualization  -  Node mapping  -  NP-hard  -  Physical network  -  Substrate networks  -  Virtual networks
  Classification code:  921 Mathematics -  913 Production Planning and Control; Manufacturing -  902.1 Engineering Graphics -  723.1 Computer Programming -  723 Computer Software, Data Handling and Applications -  722.4 Digital Computers and Systems -  715 Electronic Equipment, General Purpose and Industrial
  DOI:  10.1109/CECNet.2012.6201795
  Database:  Compendex
Compilation and indexing terms, © 2012 Elsevier Inc.