NDLI: Bandwidth prediction research based on BP neural networks in softswitch power dispatching network

Content Provider	IEEE Xplore Digital Library
Author	Jun-hong Ni Nan-nan Sun Zong-wei Duan
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Commun. Eng., North China Electr. Power Univ., Baoding, China (Jun-hong Ni; Nan-nan Sun; Zong-wei Duan)
Abstract	Softswitch is a technology that the call controlling function are detached from the media gateway. As a new switch technology which is developing quickly, it has standardized interface, strong flexibility and open service. A reasonable allocation of bandwidth resources is necessary when building softswitch network. In softswitch network, the signaling stream is responsible for the transmission of signaling data which requires high security, reliability and low latency. So it seemed appropriate to make a prediction of the signaling bandwidth. By introducing the artificial neural network, the back-propagation(BP) neural network model can rationally solve the problem of prediction. The results show that when number of calls and average call duration per day were fed into the BP network the accuracy of bandwidth prediction is higher compared with it when the input factors were fed into the network individually. The BP neural network model can effectively predict the bandwidth of signaling stream in softswitch network and thus it well have some help to the bandwidth resources allocation when building a softswitch network.
Starting Page	476
Ending Page	478
File Size	96683
Page Count	3
File Format	PDF
ISBN	9781479939855
e-ISBN	9781479902453
DOI	10.1109/ICIII.2013.6703624
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Soft switching Neural networks Neurons Bandwidth Logic gates Media Softswitch bandwidth prediction Business BP Neural Networks
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Research of the multi-service model based on softswitch in coal mine

Adapted of full- layered Softswitch network architecture

Design of video surveillance platform based on softswitch technology

Simulation of assignment problem based on BP and RBF neural network

Spares Consumption Prediction Based on BP Neural Network

Power state prediction of battery based on BP neural network

Research on the short-term traffic flow prediction method based on BP neural networks

Study on traffic accidents prediction based on BP neural network

Research on prediction model of bending force based on BP neural network with LM algorithm

Bandwidth prediction research based on BP neural networks in softswitch power dispatching network

Similar Documents

Research of the multi-service model based on softswitch in coal mine

Adapted of full- layered Softswitch network architecture

Design of video surveillance platform based on softswitch technology

Simulation of assignment problem based on BP and RBF neural network

Spares Consumption Prediction Based on BP Neural Network

Power state prediction of battery based on BP neural network

Research on the short-term traffic flow prediction method based on BP neural networks

Study on traffic accidents prediction based on BP neural network

Research on prediction model of bending force based on BP neural network with LM algorithm

Bandwidth prediction research based on BP neural networks in softswitch power dispatching network