A prediction-based dynamic resource management approach for network virtualization

Li, Jiacong; Wang, Ying; Wu, Zhanwei; Feng, Sixiang; Qiu, Xuesong

doi:10.23919/cnsm.2017.8255980

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…i means SDN network resource information. The IBD of the controller placed on the network through Expression (1) generates the information of the controller distributed to the SDN as shown in Expression (2).…”

Section: Create Controller Informationmentioning

confidence: 99%

“…In particular, the recent exponential growth of tablets and cell phones has transformed the work of institutions and managers into an environment that individuals can handle. Companies such as Amazon, Google, Microsoft and Rackspac, which also offer cloud services, are offering cloud services individually to institutions or individuals [2][3].…”

Section: Introductionmentioning

confidence: 99%

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MLMBN mechanism optimizes network load balance using information with multiple controllers

Jeong¹

2020

Ijemr

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Background/Objectives: In this paper, we propose a Deep Learning Mechanism (DLMBN) mechanism (Deep Learning Mechanism on Blockchain) that optimizes the load balance that can occur in the network by deep learning some important information related to the load balance after connecting the information of multiple distributed controllers into the blockchain. Methods/Statistical analysis: The proposed mechanism binds and manages the load of each controller distributed over the network with a blockchain, thus reducing load time while dynamically balancing the load balance. In particular, deep learning technology was used to ensure that each controller classified as a group would not be biased to one side and would maintain a balanced load balance across the entire network. Findings: As a result of the experiment, the proposed mechanism improved the load balance retention time by 14.6% on average compared to the mechanism previously studied, and the efficiency of SDNs processed in multiple groups by 17.3% on average. In addition, the overhead of SDNs for each group was lowered by 7.9%. Improvements/Applications: Based on the results of this study, future studies plan to apply the results to the actual network and test whether the performance analysis results are applicable to heterogeneous networks consisting of heterogeneous devices.

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Section: Create Controller Informationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MLMBN mechanism optimizes network load balance using information with multiple controllers

Jeong¹

2020

Ijemr

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“…In paper (Li et al, 2017) authors focused on the fact that virtual networks share the same physical network. However, the resources of the physical network are limited.…”

Section: Introductionmentioning

confidence: 99%

The Method of Determining the Optimal Transmission Resources Distribution of ICT Networks Modelled by Graphs

Bujnowski

Marciniak

et al. 2021

Transport and Telecommunication Journal

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The paper discusses the method of improvement of transmission properties of ICT networks by setting the correct distribution of transmission resources in order that it is possible to increase the resulting global probability of supporting the calls generated in the nodes included in the network. The method uses some parts of the graph theory. A minimum length path searching algorithm was used which made it possible to calculate the volume of movement transferred by individual edges of the graph describing the network. The coefficient of the distribution of transmission resources was determined and used to calculate the value of the resources in reference to a particular link, both in the case of equal and diverse movement generated in individual network nodes. A piece of software was developed which uses the results of applying the above-mentioned algorithm to prepare the files describing the analyzed structures in order to carry out simulation tests. The views and analyses are illustrated by examples, and the resulting effects of the influence of the introduction of the method of dividing network resources into transmission properties of a network modelled by graphs are shown in the charts included.

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A prediction-based dynamic resource management approach for network virtualization

Cited by 2 publications

References 12 publications

MLMBN mechanism optimizes network load balance using information with multiple controllers

MLMBN mechanism optimizes network load balance using information with multiple controllers

The Method of Determining the Optimal Transmission Resources Distribution of ICT Networks Modelled by Graphs

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