A generalized resource allocation framework in support of multi-layer virtual network embedding based on SDN

被引:17
作者
Huu Thanh Nguyen [1 ]
Anh Vu Vu [2 ]
Duc Lam Nguyen [1 ]
Van Huynh Nguyen [1 ]
Manh Nam Tran [1 ]
Quynh Thu Ngo [2 ]
Thu-Huong Truong [1 ]
Tai Hung Nguyen [1 ]
Magedanz, Thomas [3 ]
机构
[1] Hanoi Univ Sci & Technol, Sch Elect & Telecommun, Hanoi, Vietnam
[2] Hanoi Univ Sci & Technol, Sch Informat & Commun Technol, Hanoi, Vietnam
[3] Tech Univ Berlin, Dept Telecommun Syst, Berlin, Germany
关键词
Virtual network embedding; Resource allocation and management; SDN; Open Flow; Infrastructure as a Service;
D O I
10.1016/j.comnet.2015.09.042
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Network Virtualization (NV) allows multiple heterogeneous architectures to simultaneously coexist in a shared infrastructure. Embedding multiple virtual networks (VNs) in a shared substrate deals with efficient mapping of virtual resources in the physical infrastructure and is referred to as the Virtual Network Embedding problem (VNE-problem). Although there is recently a number of research work in the area of network virtualization based on the Software-Defined Networking (SDN) technology, virtual network embedding in SDN remains challenging from both theoretical and practical points of view. This article focuses on virtual network embedding strategies and related issues for Infrastructure-as-a-Service (laaS) paradigms under the constraint of fixed virtual node locations. Special considerations are given to the problems related to resource allocation and link sharing of multi-layer virtual networks on top of the physical substrate. Firstly, a heuristic virtual network embedding algorithm is proposed that can improve the mapping acceptance ratio and resource efficiency in the laaS context. Secondly, REsource reSERvation in generalized Virtual NETworks (ReServNet), a Software-Defined Networking platform designed for embedding multi-level virtual networks in physical infrastructures is developed. By defining new softwarized logical functions, ReServNet allows network administrators to create and manage multiple virtual networks on top of the physical network and allocate bandwidth resources to them accordingly. Moreover, the ReServNet framework allows for designing, prototyping, benchmarking and evaluating the performance of different network embedding algorithms easily in real SDN virtualization environments. Different issues related to virtual network embedding on SDN-based physical substrate are also analyzed and discussed in detail. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:251 / 269
页数:19
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[41]   Virtual Network Embedding Over Multi-Band Elastic Optical Network Based on Cross-Matching Mechanism and Hypergraph Theory [J].
Yang, Zeyuan ;
Gu, Rentao ;
Ji, Yuefeng .
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2023, 20 (04) :4681-4697
[42]   Memetic Multi-Objective Particle Swarm Optimization-Based Energy-Aware Virtual Network Embedding [J].
Shahin, Ashraf A. .
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2015, 6 (04) :35-46
[43]   Experimental Demonstration of a Packet-based Protection for Seamlessly Recovering from a Multi-layer Metro Network Fronthaul Failure [J].
Kondepu, K. ;
Ramanathan, S. ;
Tacca, M. ;
Razo, M. ;
Mirkhanzadeh, B. ;
Giannone, F. ;
Valcarenghi, L. ;
Fumagalli, A. .
IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM 2019 WKSHPS), 2019, :906-+
[44]   MUVINE: Multi-Stage Virtual Network Embedding in Cloud Data Centers Using Reinforcement Learning-Based Predictions [J].
Thakkar, Hiren Kumar ;
Dehury, Chinmaya Kumar ;
Sahoo, Prasan Kumar .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2020, 38 (06) :1058-1074
[45]   Space-Air-Ground Integrated Multi-Domain Network Resource Orchestration Based on Virtual Network Architecture: A DRL Method [J].
Zhang, Peiying ;
Wang, Chao ;
Kumar, Neeraj ;
Liu, Lei .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (03) :2798-2808
[46]   Performance Improvement of a Virtual Network Embedding Algorithm based on Temporal-difference Learning by Resource-Constraint-Aware Candidate Solution Selection [J].
Fukushima Y. ;
Sagawa Y. ;
Tarutani Y. ;
Yokohira T. .
IEIE Transactions on Smart Processing and Computing, 2024, 13 (02) :158-166
[47]   VNE2: A Virtual Network Embedding Framework Based on Equivalent Bandwidth in Fiber-Wireless Enhanced 5G Networks [J].
Han, Pengchao ;
Guo, Lei ;
Liu, Yejun .
2020 22ND INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON 2020), 2020,
[48]   Multi-Stage Learning Framework Using Convolutional Neural Network and Decision Tree-Based Classification for Detection of DDoS Pandemic Attacks in SDN-Based SCADA Systems [J].
Polat, Onur ;
Turkoglu, Muammer ;
Polat, Huseyin ;
Oyucu, Saadin ;
Uzen, Huseyin ;
Yardimci, Fahri ;
Aksoz, Ahmet .
SENSORS, 2024, 24 (03)
[49]   Joint Q-Learning Based Resource Allocation and Multi-Numerology B5G Network Slicing Exploiting LWA Technology [J].
Elmosilhy, Noha A. ;
Elmesalawy, Mahmoud M. ;
Ibrahim, Ibrahim I. ;
Abd El-Haleem, Ahmed M. .
IEEE ACCESS, 2024, 12 :22043-22058