NDLI: An optimal neural network based call admission control protocol for high-speed networks: modeling and analysis

Content Provider	IEEE Xplore Digital Library
Author	Madubata, C. Arozullah, M.
Copyright Year	2003
Description	Author affiliation: Tuskegee Univ., AL, USA (Madubata, C.)
Abstract	Presents the development, modeling, analysis and performance evaluation of an optimal neural network based call admission control (CAC) protocol for high-speed Broadband Integrated Services Digital Networks. Thus neural network based CAC protocol simultaneously satisfies two quality of service (QoS) parameters, namely cell loss ratio (CLR) and delay. The protocol presented is suitable for "on-line" application and provides efficient network resource (buffer space and link capacity) utilization. The end-to-end delay and CLR values are divided among the nodes of the connection. For Poisson and ON-OFF sources, M/D/1/K and MMPP/D/1/K queuing models are developed. Analytical expressions at nodes for CLR and delay have are developed based on these models. These analytical expressions are used to develop a CAC protocols. The principles behind the Kohonen neural networks were used in the development and software implementation of this CAC protocol.
Sponsorship	Lane Dept. Comput. Sci. & Electr. Eng. Electr. & Comput. Eng., WVU Inst. Technol. Adv. Power Eng. Res. Center IEEE Control Syst. Soc. IEEE West Virginia Sect
Starting Page	153
Ending Page	157
File Size	332625
Page Count	5
File Format	PDF
ISBN	0780376978
ISSN	00942898
DOI	10.1109/SSST.2003.1194548
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-03-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Call admission control Protocols High-speed networks Delay Mathematical model Quality of service Queueing analysis Artificial intelligence Performance analysis
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

A deterministic call admission control protocol for bursty traffic in high-speed networks: modeling and analysis

Call admission control in ATM networks with the random neural network

Performance evaluation of MS/TP protocol on service delay

Performance Analysis and Enhancement for Priority Based IEEE 802.11 Network

Neural-network-based call admission control in ATM networks with heterogeneous arrivals

Call-level and packet-level performance modeling in cellular CDMA networks

Machine learning based Call Admission Control approaches: A comparative study

An improvement of eoS mechanism for wireless network

E-limited scheduling in Bluetooth piconets: performance and admission control

An optimal neural network based call admission control protocol for high-speed networks: modeling and analysis

Similar Documents

A deterministic call admission control protocol for bursty traffic in high-speed networks: modeling and analysis

Call admission control in ATM networks with the random neural network

Performance evaluation of MS/TP protocol on service delay

Performance Analysis and Enhancement for Priority Based IEEE 802.11 Network

Neural-network-based call admission control in ATM networks with heterogeneous arrivals

Call-level and packet-level performance modeling in cellular CDMA networks

Machine learning based Call Admission Control approaches: A comparative study

An improvement of eoS mechanism for wireless network

E-limited scheduling in Bluetooth piconets: performance and admission control

An optimal neural network based call admission control protocol for high-speed networks: modeling and analysis