PAME: Evolutionary membrane computing for virtual network embedding

Abstract Virtual network embedding is an NP-hard online problem, partially due to diversity effects during mapping. Mapping diversity is critical not only for single virtual network but also for a set of online virtual networks. Two common ways, using heuristic information or using extra constraints, are employed to reduce the problem of hardness. Both restrict diversity during mapping. A preferable technique is executing parallel scatter mapping in the solution space, which can promote mapping quality while maintaining diversity. This technique is challenging due to a nested paralleling. Using membrane computing, we designed a P system with active non-elementary membranes (PAME). With a specific membrane structure, PAME achieves nested paralleling via a dual-parallel mapping stage. The stage couples an inter-increment parallel with an intra-increment one, relying on non-elementary membrane self-division and elementary membrane bootstrap. Simulation experiments showed that PAME outperformed existing algorithms in long-term average revenue, acceptance ratio, and long-term revenue-to-cost ratio.

[1]  Xavier Hesselbach,et al.  A distributed, parallel, and generic virtual network embedding framework , 2013, 2013 IEEE International Conference on Communications (ICC).

[2]  Minlan Yu,et al.  Rethinking virtual network embedding: substrate support for path splitting and migration , 2008, CCRV.

[3]  Djamal Zeghlache,et al.  A Distributed and Autonomic Virtual Network Mapping Framework , 2008, Fourth International Conference on Autonomic and Autonomous Systems (ICAS'08).

[4]  Xiang Cheng,et al.  A unified enhanced particle swarm optimization‐based virtual network embedding algorithm , 2013, Int. J. Commun. Syst..

[5]  Juanjuan He,et al.  A hybrid membrane evolutionary algorithm for solving constrained optimization problems , 2014 .

[6]  Yunyun Niu,et al.  A Uniform Solution for Vertex Cover Problem by Using Time-Free Tissue P Systems , 2015, BIC-TA.

[7]  Daniel Díaz-Pernil,et al.  Segmenting images with gradient-based edge detection using Membrane Computing , 2013, Pattern Recognit. Lett..

[8]  Xavier Hesselbach,et al.  Energy Efficient Virtual Network Embedding , 2012, IEEE Communications Letters.

[9]  Jonathan S. Turner,et al.  Diversifying the Internet , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[10]  Xiang Cheng,et al.  Virtual network embedding through topology-aware node ranking , 2011, CCRV.

[11]  Peng Xu,et al.  Energy aware virtual network embedding with dynamic demands: Online and offline , 2015, Comput. Networks.

[12]  Andreas Fischer,et al.  A simulation framework for Virtual Network Embedding algorithms , 2014, 2014 16th International Telecommunications Network Strategy and Planning Symposium (Networks).

[13]  Holger Karl,et al.  A virtual network mapping algorithm based on subgraph isomorphism detection , 2009, VISA '09.

[14]  Xiang Cheng,et al.  Energy-Aware Virtual Network Embedding , 2014, IEEE/ACM Transactions on Networking.

[15]  David G. Andersen,et al.  Theoretical Approaches to Node Assignment , 2002 .

[16]  Mario J. Pérez-Jiménez,et al.  A uniform family of tissue P systems with cell division solving 3-COL in a linear time , 2008, Theor. Comput. Sci..

[17]  Jian-hua Xiao,et al.  A membrane evolutionary algorithm for DNA sequence design in DNA computing , 2012 .

[18]  Ellen W. Zegura,et al.  How to model an internetwork , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[19]  Yong Zhu,et al.  Algorithms for Assigning Substrate Network Resources to Virtual Network Components , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[20]  Gheorghe Paun,et al.  Computing with Membranes , 2000, J. Comput. Syst. Sci..

[21]  Lixin Gao,et al.  How to lease the internet in your spare time , 2007, CCRV.

[22]  Raouf Boutaba,et al.  ViNEYard: Virtual Network Embedding Algorithms With Coordinated Node and Link Mapping , 2012, IEEE/ACM Transactions on Networking.

[23]  Gheorghe Paun,et al.  A quick introduction to membrane computing , 2010, J. Log. Algebraic Methods Program..

[24]  Mario J. Pérez-Jiménez,et al.  Solving the Independent Set Problem by Using Tissue-Like P Systems with Cell Division , 2009, IWINAC.

[25]  Xavier Hesselbach,et al.  Virtual Network Embedding: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[26]  Scott Shenker,et al.  Overcoming the Internet impasse through virtualization , 2005, Computer.

[27]  Javier Jiménez,et al.  Network virtualization: a view from the bottom , 2009, VISA '09.

[28]  Guy Pujolle,et al.  A new virtual network static embedding strategy within the Cloud's private backbone network , 2014, Comput. Networks.

[29]  Guy Pujolle,et al.  VNE-AC: Virtual Network Embedding Algorithm Based on Ant Colony Metaheuristic , 2011, 2011 IEEE International Conference on Communications (ICC).

[30]  Ning Wang,et al.  A bio-inspired algorithm based on membrane computing and its application to gasoline blending scheduling , 2011, Comput. Chem. Eng..

[31]  Ibrahim Matta,et al.  A decomposition-based architecture for distributed virtual network embedding , 2014, DCC '14.

[32]  Raouf Boutaba,et al.  Network virtualization: state of the art and research challenges , 2009, IEEE Communications Magazine.