Performance-aware placement and chaining scheme for virtualized network functions: a particle swarm optimization approach

被引:6
|
作者
Asgari, Samane [1 ]
Jamali, Shahram [1 ,3 ]
Fotohi, Reza [2 ]
Nooshyar, Mahdi [1 ]
机构
[1] Univ Mohaghegh Ardabili, Comp Engn Dept, Ardebil, Iran
[2] Shahid Beheshti Univ, Fac Comp Sci & Engn, GC Evin, Tehran 1983969411, Iran
[3] Iran Univ Sci & Technol, Ctr Excellence Future Networks, Tehran, Iran
来源
JOURNAL OF SUPERCOMPUTING | 2021年 / 77卷 / 11期
关键词
Network functions virtualization (NFV); Virtualized network functions (VNFs) placement and chaining; Particle swarm optimization; ALGORITHM; PSO;
D O I
10.1007/s11227-021-03758-9
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Network functions virtualization (NFV) is a new concept that has received the attention of both researchers and network providers. NFV decouples network functions from specialized hardware devices and virtualizes these network functions as software instances called virtualized network functions (VNFs). NFV leads to various benefits, including more flexibility, high resource utilization, and easy upgrades and maintenances. Despite recent works in this field, placement and chaining of VNFs need more attention. More specifically, some of the existing works have considered only the placement of VNFs and ignored the chaining part. So, they have not provided an integrated view of host or bandwidth resources and propagation delay of paths. In this paper, we solve the VNF placement and chaining problem as an optimization problem based on the particle swarm optimization (PSO) algorithm. Our goal is to minimize the required number of used servers, the average propagation delay of paths, and the average utilization of links while meeting network demands and constraints. Based on the obtained results, the algorithm proposed in this study can find feasible and high-quality solutions.
引用
收藏
页码:12209 / 12229
页数:21
相关论文
共 50 条
  • [1] Performance-aware placement and chaining scheme for virtualized network functions: a particle swarm optimization approach
    Samane Asgari
    Shahram Jamali
    Reza Fotohi
    Mahdi Nooshyar
    [J]. The Journal of Supercomputing, 2021, 77 : 12209 - 12229
  • [2] Particle Swarm Optimization for Energy-Aware Virtual Machine Placement Optimization in Virtualized Data Centers
    Wang, Shangguang
    Liu, Zhipiao
    Zheng, Zibin
    Sun, Qibo
    Yang, Fangchun
    [J]. 2013 19TH IEEE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS 2013), 2013, : 102 - 109
  • [3] Machine Learning for Performance-Aware Virtual Network Function Placement
    Manias, Dimitrios Michael
    Jammal, Manar
    Hawilo, Hassan
    Shami, Abdallah
    Heidari, Parisa
    Larabi, Adel
    Brunner, Richard
    [J]. 2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [4] Performance-aware Energy Optimization on Mobile Devices in Cellular Network
    Cui, Yong
    Xiao, Shihan
    Wang, Xin
    Li, Minming
    Wang, Hongyi
    Lai, Zeqi
    [J]. 2014 PROCEEDINGS IEEE INFOCOM, 2014, : 1123 - 1131
  • [5] A Reinforcement Learning Approach for Placement of Stateful Virtualized Network Functions
    Kibalya, Godfrey
    Serrat, Joan
    Gorricho, Juan-Luis
    Bujjingo, Doreen Gift
    Sserugunda, Jonathan
    Zhang, Peiying
    [J]. 2021 IFIP/IEEE INTERNATIONAL SYMPOSIUM ON INTEGRATED NETWORK MANAGEMENT (IM 2021), 2021, : 672 - 676
  • [6] Contention-Aware Performance Prediction For Virtualized Network Functions
    Manousis, Antonis
    Sharma, Rahul Anand
    Sekar, Vyas
    Sherry, Justine
    [J]. SIGCOMM '20: PROCEEDINGS OF THE 2020 ANNUAL CONFERENCE OF THE ACM SPECIAL INTEREST GROUP ON DATA COMMUNICATION ON THE APPLICATIONS, TECHNOLOGIES, ARCHITECTURES, AND PROTOCOLS FOR COMPUTER COMMUNICATION, 2020, : 270 - 282
  • [7] Performance-Aware Energy Optimization on Mobile Devices in Cellular Network
    Cui, Yong
    Xiao, Shihan
    Wang, Xin
    Lai, Zeqi
    Yang, Zhenjie
    Li, Minming
    Wang, Hongyi
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2017, 16 (04) : 1073 - 1089
  • [8] A New Approach on Particle Swarm Optimization for Multimodal Functions
    Afsahi, Zahra
    Meybodi, MohammadReza
    [J]. 2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 1, 2009, : 303 - +
  • [9] Well Placement Optimization Using a Particle Swarm Optimization Algorithm, a Novel Approach
    Afshari, S.
    Pishvaie, M. R.
    Aminshahidy, B.
    [J]. PETROLEUM SCIENCE AND TECHNOLOGY, 2014, 32 (02) : 170 - 179
  • [10] PAPSO: A Power-Aware VM Placement Technique Based on Particle Swarm Optimization
    Ibrahim, Abdelhameed
    Noshy, Mostafa
    Ali, Hesham Arafat
    Badawy, Mahmoud
    [J]. IEEE ACCESS, 2020, 8 : 81747 - 81764