TR202104311A2 - METHOD TO SOLVE THE VIRTUAL NETWORK EMBEDDING PROBLEM IN 5G AND BEYOND NETWORKS BY DEEP INFORMATION MAXIMIZATION USING MULTI-PHYSICAL NETWORK - Google Patents

METHOD TO SOLVE THE VIRTUAL NETWORK EMBEDDING PROBLEM IN 5G AND BEYOND NETWORKS BY DEEP INFORMATION MAXIMIZATION USING MULTI-PHYSICAL NETWORK

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Publication number
TR202104311A2
TR202104311A2 TR2021/004311A TR202104311A TR202104311A2 TR 202104311 A2 TR202104311 A2 TR 202104311A2 TR 2021/004311 A TR2021/004311 A TR 2021/004311A TR 202104311 A TR202104311 A TR 202104311A TR 202104311 A2 TR202104311 A2 TR 202104311A2
Authority
TR
Turkey
Prior art keywords
solve
virtual network
physical network
deep information
information maximization
Prior art date
Application number
TR2021/004311A
Other languages
Turkish (tr)
Inventor
Bayramli Yeşi̇m
Çağri Güngör Vehbi̇
Coşkun Mustafa
Original Assignee
Havelsan Hava Elektronik Sanayi Ve Ticaret Anonim Sirketi
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Havelsan Hava Elektronik Sanayi Ve Ticaret Anonim Sirketi filed Critical Havelsan Hava Elektronik Sanayi Ve Ticaret Anonim Sirketi
Priority to TR2021/004311A priority Critical patent/TR202104311A2/en
Publication of TR202104311A2 publication Critical patent/TR202104311A2/en
Priority to PCT/TR2022/050191 priority patent/WO2022186808A1/en

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/02—Details
    • H04L12/12—Arrangements for remote connection or disconnection of substations or of equipment thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Image Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

Bu buluş, 5G ve ötesi ağlar için sanal ağ gömme (virtual network embedding (VNE)) problemini çözen ve çoklu fiziksel ağ yapısını kullanan bir derin öğrenme temelli ağ gömme algoritması ile ilgilidir. VNE probleminin çözümünde kullanılması için DGI ile çözülmesi ve Laplacian matrisleri yerine yakınsama ölçülerinin matris halleri ile latent vektörler oluşturulmaktadır.The present invention relates to a deep learning-based network embedding algorithm that uses multiple physical network structure and solves the virtual network embedding (VNE) problem for 5G and beyond networks. In order to be used in solving the VNE problem, latent vectors are created by solving it with DGI and by matrix states of convergence measures instead of Laplacian matrices.

TR2021/004311A 2021-03-05 2021-03-05 METHOD TO SOLVE THE VIRTUAL NETWORK EMBEDDING PROBLEM IN 5G AND BEYOND NETWORKS BY DEEP INFORMATION MAXIMIZATION USING MULTI-PHYSICAL NETWORK TR202104311A2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
TR2021/004311A TR202104311A2 (en) 2021-03-05 2021-03-05 METHOD TO SOLVE THE VIRTUAL NETWORK EMBEDDING PROBLEM IN 5G AND BEYOND NETWORKS BY DEEP INFORMATION MAXIMIZATION USING MULTI-PHYSICAL NETWORK
PCT/TR2022/050191 WO2022186808A1 (en) 2021-03-05 2022-03-03 Method for solving virtual network embedding problem in 5g and beyond networks with deep information maximization using multiple physical network structure

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
TR2021/004311A TR202104311A2 (en) 2021-03-05 2021-03-05 METHOD TO SOLVE THE VIRTUAL NETWORK EMBEDDING PROBLEM IN 5G AND BEYOND NETWORKS BY DEEP INFORMATION MAXIMIZATION USING MULTI-PHYSICAL NETWORK

Publications (1)

Publication Number Publication Date
TR202104311A2 true TR202104311A2 (en) 2021-04-21

Family

ID=76503043

Family Applications (1)

Application Number Title Priority Date Filing Date
TR2021/004311A TR202104311A2 (en) 2021-03-05 2021-03-05 METHOD TO SOLVE THE VIRTUAL NETWORK EMBEDDING PROBLEM IN 5G AND BEYOND NETWORKS BY DEEP INFORMATION MAXIMIZATION USING MULTI-PHYSICAL NETWORK

Country Status (2)

Country Link
TR (1) TR202104311A2 (en)
WO (1) WO2022186808A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115499512B (en) * 2022-11-18 2023-01-17 长沙容数信息技术有限公司 Efficient resource allocation method and system based on super-fusion cloud virtualization

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108989122B (en) * 2018-08-07 2019-04-16 北京邮电大学 Virtual network requests mapping method, device and realization device
CN109327340B (en) * 2018-11-16 2021-10-29 福州大学 Mobile wireless network virtual network mapping method based on dynamic migration
CN110233763B (en) * 2019-07-19 2021-06-18 重庆大学 Virtual network embedding algorithm based on time sequence difference learning
CN112436992B (en) * 2020-11-10 2022-01-25 北京邮电大学 Virtual network mapping method and device based on graph convolution network

Also Published As

Publication number Publication date
WO2022186808A1 (en) 2022-09-09

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