Two Efficient QoS-Based Approaches for a Resource Splitting Strategy across Multiple Cloud Providers

In this paper, we address the problem of com-putational and networking virtual resources embedding across multiple Infrastructure-as-a-Service (IaaS) providers. This issue, usually referred to as the Virtual Network Embedding (VNE) problem, requires two phases of operation in such a context: the multicloud virtual network requests (VNRs) splitting, followed by the intracloud VNR segments mapping. This paper focuses on the splitting phase problem, by proposing a splitting strategy based on two optimization approaches, with the objective of improving the performance and the quality of service (QoS) of resulting mapped VNR segments. An Integer Linear Program (ILP) is used to formalize our splitting strategy as a mathematical minimization problem with constraints. The ILP model is first solved with the exact approach. Subsequently, a metaheuristic approach based on the Tabu Search (TS) is proposed in order to find optimal or near-optimal solutions in polynomial solving time. The simulation results obtained show the efficiency of the proposed VNRs splitting approaches according to several performance criteria. Solution costs of the heuristic are on average close to the exact solution, with an average cost gap ranging from 0% to a maximum of 2.05%, performed in a highly reduced computing time. In comparison with other baseline approaches, the acceptance rate and the delay are improved by approximately 15%, while preventing QoS violations.

[1]  Bo Lv,et al.  Virtual Resource Organization and Virtual Network Embedding across Multiple Domains , 2010, 2010 International Conference on Multimedia Information Networking and Security.

[2]  Ahmed Amokrane,et al.  Greenhead: Virtual Data Center Embedding across Distributed Infrastructures , 2013, IEEE Transactions on Cloud Computing.

[3]  Rubén S. Montero,et al.  IaaS Cloud Architecture: From Virtualized Datacenters to Federated Cloud Infrastructures , 2012, Computer.

[4]  Kadangode K. Ramakrishnan,et al.  Structural Overview of ISP Networks , 2010 .

[5]  Jian Yang,et al.  Cost-Efficient Provisioning Strategy for Multiple Services in Distributed Clouds , 2016, 2016 International Conference on Cloud Computing Research and Innovations (ICCCRI).

[6]  Mohammed Samaka,et al.  Multi-cloud Distribution of Virtual Functions and Dynamic Service Deployment: Open ADN Perspective , 2015, 2015 IEEE International Conference on Cloud Engineering.

[7]  Raouf Boutaba,et al.  PolyViNE: policy-based virtual network embedding across multiple domains , 2010, VISA '10.

[8]  Jing Chen,et al.  Survivable virtual network embedding across multiple domains , 2016, 2016 2nd IEEE International Conference on Computer and Communications (ICCC).

[9]  Ken Chen,et al.  A Cloud-Oriented Algorithm for Virtual Network Embedding over Multi-Domain , 2016, 2016 IEEE 41st Conference on Local Computer Networks Workshops (LCN Workshops).

[10]  Jianqiang Ma,et al.  Resource management framework for virtual data center embedding based on software defined networking , 2017, Comput. Electr. Eng..

[11]  Raouf Boutaba,et al.  Multi-Path Link Embedding for Survivability in Virtual Networks , 2016, IEEE Transactions on Network and Service Management.

[12]  Symeon Papavassiliou,et al.  Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning , 2013, IEEE Transactions on Parallel and Distributed Systems.

[13]  Bu-Sung Lee,et al.  Optimization of Resource Provisioning Cost in Cloud Computing , 2012, IEEE Transactions on Services Computing.

[14]  Sunilkumar S. Manvi,et al.  Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey , 2014, J. Netw. Comput. Appl..

[15]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[16]  Djamal Zeghlache,et al.  Virtual network provisioning across multiple substrate networks , 2011, Comput. Networks.

[17]  Brunilde Sansò,et al.  A Tabu Search Algorithm for the Location of Data Centers and Software Components in Green Cloud Computing Networks , 2013, IEEE Transactions on Cloud Computing.

[18]  Rajkumar Buyya,et al.  Inter‐Cloud architectures and application brokering: taxonomy and survey , 2014, Softw. Pract. Exp..

[19]  Osamu Akashi,et al.  Efficient virtual network optimization across multiple domains without revealing private information , 2014, 2014 23rd International Conference on Computer Communication and Networks (ICCCN).

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

[21]  Jie Wu,et al.  Virtual Network Embedding with Opportunistic Resource Sharing , 2014, IEEE Transactions on Parallel and Distributed Systems.

[22]  Djamal Zeghlache,et al.  Exact and Heuristic Resource Mapping Algorithms for Distributed and Hybrid Clouds , 2017, IEEE Transactions on Cloud Computing.

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

[24]  Rachida Dssouli,et al.  A service oriented broker-based approach for dynamic resource discovery in virtual networks , 2015, Journal of Cloud Computing.

[25]  M. N. Shanmukha Swamy,et al.  Simulated Annealing and Tabu Search Algorithms for Multiway Graph Partition , 1992, J. Circuits Syst. Comput..

[26]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[27]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[28]  David Dietrich,et al.  Multi-Provider Virtual Network Embedding With Limited Information Disclosure , 2015, IEEE Transactions on Network and Service Management.

[29]  Xuan Wang,et al.  Resource provision algorithms in cloud computing: A survey , 2016, J. Netw. Comput. Appl..

[30]  Tolga Ovatman,et al.  Network-aware embedding of virtual machine clusters onto federated cloud infrastructure , 2016, J. Syst. Softw..

[31]  Laura A. Sanchis,et al.  Multiple-Way Network Partitioning , 1989, IEEE Trans. Computers.