User-driven Call Admission Control for VoIP over WLAN with a Neural Network based cognitive engine
Abstract
In this paper we deal with the problem of user-driven Call Admission Control for Voice over IP communications in a Wireless LAN environment. We argue that state-of-the-art solutions to this problem are suboptimal, since they leverage on analytical models whose assumptions are not necessarily verified in the scenario considered. To overcome this problem, we propose a cognitive solution based on Multilayer Feed-forward Neural Networks. According to our solution, the mobile station learns from past experience how application-layer service quality depends on the wireless link conditions. Our performance evaluation, carried out both by simulation and testbed experiments, shows that this solution effectively outperforms state-of-the-art strategies in performing a correct admission decision.
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Admission control has leveraged ML extensively in a variety of networks, including ATM networks, wireless networks, cellular networks, ad hoc networks, and next generation networks.
“As shown in Table 14, Admission control has leveraged ML extensively in a variety of networks, including ATM networks [95,189,190], wireless networks [8,36,359], cellular networks [66,67,281,372,458], ad hoc networks [452], and next generation networks [311].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [36]
Baldo et al. report 98.5% and 92% accuracy for offline and online learning, respectively.
“The authors report 98.5% and 92% accuracy for offline and online learning, respectively.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [36]
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Cognitive Call Admission Control for VoIP over IEEE 802.11 Using Bayesian Networks
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Self-citationAdmission Control of Video Sessions over Ad Hoc Networks Using Neural Classifiers
Vassis, D., Kampouraki, A., Belsis, P., & Skourlas, C. (2014) · 2014 IEEE Military Communications Conference · doi:10.1109/milcom.2014.173 · Cited by 7 · see citing works
- Authors
- Baldo, N., Dini, P., & Nin-Guerrero, J.
- Affiliations
- Centre Tecnologic de Telecomunicacions de Catalunya (ES)
- ORCID
- Dini, Paolo
- Venue
- 2010 2nd International Workshop on Cognitive Information Processing
- Publisher
- IEEE
- Published
- 2010-06
- Pages
- 52-56
- OpenAlex
- W2061946694
- Cited by
- 10
- References
- 15
- Citations by year
- 2023: 2 · 2022: 2 · 2018: 2 · 2015: 1 · 2014: 1 · 2013: 1
- FWCI
- 0.58
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Workshop on Cognitive Information Processing (CIP) (publishedVersion)
- Funders
- Ministerio de Ciencia e Innovación
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Networks and Protocols
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Communication Networks Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Network Optimization
- Keywords
- call admission control, VoIP, wireless LAN, cognitive radio, multilayer perceptron
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