Distributed Virtual Network Embedding System with Historical Archives and Set-Based Particle Swarm Optimization

An SONG, Wei-Neng CHEN, Tianlong GU, Huaqiang YUAN, Sam KWONG, Jun ZHANG

Research output: Journal PublicationsJournal Article (refereed)peer-review

50 Citations (Scopus)

Abstract

Virtual network embedding (VNE) is an important problem in network virtualization for the flexible sharing of network resources. While most existing studies focus on centralized embedding for VNE, distributed embedding is considered more scalable and suitable for large-scale scenarios, but how virtual resources can be mapped to substrate resources effectively and efficiently remains a challenging issue. In this paper, we devise a distributed VNE system with historical archives (HAs) and metaheuristic approaches. First, we introduce metaheuristic approaches to each delegation of the distributed embedding system as the optimizer for VNE. Compared to the heuristic-based greedy algorithms used in existing distributed embedding approaches, which are prone to be trapped in local optima, metaheuristic approaches can provide better embedding performance for these distributed delegations. Second, an archive-based strategy is also introduced in the distributed embedding system to assist the metaheuristic algorithms. The archives are used to record the up-to-date information of frequently repeated tasks. By utilizing such archives as historical memory, metaheuristic algorithms can further improve embedding performance for frequently repeated tasks. Following this idea, we incorporate the set-based particle swarm optimization (PSO) as the optimizer and propose the distributed VNE system with HAs and set-based PSO (HA-VNE-PSO) system to solve the VNE problem in a distributed way. HA-VNE-PSO is empirically validated in scenarios of different scales. The experimental results verify that HA-VNE-PSO can scale well with respect to substrate networks, and the HA strategy is indeed effective in different scenarios.
Original languageEnglish
Pages (from-to)927-942
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number2
Early online date3 Jan 2019
DOIs
Publication statusPublished - Feb 2021
Externally publishedYes

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under Grant 61622206, Grant 61332002, and Grant 61876111, in part by the Natural Science Foundation of Guangdong under Grant 2015A030306024, in part by the Science and Technology Plan Project of Guangdong Province under Grant 2018B050502006, in part by the Open Project Program of the State Key Laboratory of Mathematical Engineering and Advanced Computing, and in part by the Fundamental Research Funds for the Central Universities.

Keywords

  • Distributed systems
  • metaheuristic
  • particle swarm optimization (PSO)
  • virtual network embedding (VNE)

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