ATM call admission control using neural networks

Youssef, S.A.; Habib, I.; Saadawi, Tarek

doi:10.1109/milcom.1995.483260

Cited by 3 publications

(1 citation statement)

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“…In [1], Youssef, I. et al proposed a novel call admission control algorithm for ATM networks using neural networks. The aim of this paper is to achieve an efficient algorithm that allows for multiplexing gain in terms of processing and storage requirements and robustness, so that it could be suitable for all types of traffic in networks.…”

Section: Related Workmentioning

confidence: 99%

A Comparative Study of Call Admission Control in Mobile Multimedia Networks using Soft Computing

Kumar¹,

Kumar²,

Pandey³

2014

IJCA

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Call admission control (CAC) is one of challenging issues for quality of service (QoS) provisioning in mobile multimedia network communication systems. CAC can be defined as the system that restricts the network access based on resource availability. A new call is admitted if enough idle resources are available in order to meet the QoS requirements of the new call without violating the QoS for already accepted calls, otherwise the call is rejected. This paper provides a survey of different CAC schemes used for mobile multimedia networks using soft computing techniques like artificial neural networks, fuzzy logic, and genetic algorithms. Soft computing can be used to obtain optimized results from many parameters used in mobile multimedia networks. Our goal is to review and compare the best features of soft computing applied in mobile multimedia networks to improve the capability of existing CAC methods. This paper also elaborates the future directions for the use of untouched areas of artificial neural networks, fuzzy logic, and genetic algorithm.

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Section: Related Workmentioning

confidence: 99%