research-article

Admission of QoS aware users in a smart network

Authors:

Georgia Sakellari,

Maurizio D'arienzoAuthors Info & Claims

ACM Transactions on Autonomous and Adaptive Systems (TAAS), Volume 3, Issue 1

Article No.: 4, Pages 1 - 28

https://doi.org/10.1145/1342171.1342175

Published: 27 March 2008 Publication History

Abstract

Smart networks have grown out of the need for stable, reliable, and predictable networks that will guarantee packet delivery under Quality of Service (QoS) constraints. In this article we present a measurement-based admission control algorithm that helps control traffic congestion and guarantee QoS throughout the lifetime of a connection. When a new user requests to enter the network, probe packets are sent from the source to the destination to estimate the impact that the new connection will have on the QoS of both the new and the existing users. The algorithm uses a novel algebra of QoS metrics, inspired by Warshall's algorithm, to look for a path with acceptable QoS values to accommodate the new flow. We describe the underlying mathematical principles and present experimental results obtained by evaluating the method in a large laboratory test-bed operating the Cognitive Packet Network (CPN) protocol.

References

[1]

Bianchi, G., Capone, A., and Petrioli, C. 2000. Throughput analysis of end-to-end measurement-based admission control in IP. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2000). Tel Aviv, Israel, 1461--1470.

[2]

Breslau, L., Knightly, E. W., Shenker, S., Stoica, I., and Zhang, H. 2000. Endpoint admission control: architectural issues and performance. In Proceedings of ACM Special Interest Group on Data Communications (SIGCOMM 2000). Stockholm, Sweden, 57--70.

Digital Library

[3]

Cetinkaya, C. and Knightly, E. W. 2000. Egress admission control. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2000). Tel Aviv, Israel, 1471--1480.

[4]

Chen, Z., Gao, L., and Kwiat, K. 2003. Modeling the spread of active worms. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2003). San Francisco, CA, USA.

[5]

Elek, V., Karlsson, G., and Ronngren, R. 2000. Admission control based on end-to-end measurements. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2000). Vol. 2. Tel Aviv, Israel, 623--630.

[6]

Floyd, R. W. 1962. Algorithm 97: Shortest path. Comm. ACM 5, 6 (June), 345.

Digital Library

[7]

Floyd, S. 1996. Comments on measurement-based admissions control for controlled-load services. Tech. rep., Lawrence Berkeley Laboratory. (July).

[8]

Ganesh, A. J., Key, P., Polis, D., and Srikant, R. 2005. Congestion notification and probing mechanisms for endpoint admission control. IEEE/ACM Trans. Netw. 14, 3 (June), 568--578.

Digital Library

[9]

Gelenbe, E. 1993. Learning in the recurrent random neural network. Neural Computation 5, 1 (Jan.), 154--164.

Digital Library

[10]

Gelenbe, E., Gellman, M., Lent, R., Liu, P., and Su, P. 2004. Autonomous smart routing for network qos. In Proceedings of the First International Conference on Autonomic Computing (ICAC). New York, NY, 232--239.

Digital Library

[11]

Gelenbe, E., Lent, R., Montuori, A., and Xu, Z. 2002. Cognitive packet networks: QoS and performance. In Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MASCOTS'02). IEEE Computer Society, Fort Worth, TX, 3--12. Opening Keynote Paper.

Digital Library

[12]

Gelenbe, E., Lent, R., and Xu, Z. 2001. Design and performance of cognitive packet networks. Performance Evaluation 46, 2-3 (Oct.), 155--176.

Digital Library

[13]

Gelenbe, E., Mang, X., and Oenvural, R. 1996. Diffusion based statistical call admission control in ATM. Performance Evaluation 27/28, (Oct.), 411--436.

Digital Library

[14]

Gelenbe, E., Sakellari, G., and D' Arienzo, M. 2007. Controlling access to preserve QoS in a self-aware network. In Proceedings of the First IEEE International Conference on Self-Adaptive and Self-Orgnizing Systems (SASO 2007). Boston, MA.

Digital Library

[15]

Gelenbe, E., Xu, Z., and Seref, E. 1999. Cognitive packet networks. In Proceedings of the 11th International Conference on Tools with Artificial Intelligence (ICTAI '99). IEEE Computer Society Press, Chicago, IL, 47--54.

Digital Library

[16]

Gibbens, R. J. and Kelly, F. 1999. Distributed connection acceptance control for a connectionless network. In Proceedings of the 16th International Teletraffic Congress (ITC 99). Vol. 2. Edinburgh, UK, 941--52.

[17]

Gibbens, R. J., Kelly, F. P., and Key, P. B. 1995. A decision-theoretic approach to call admission control in atm networks. IEEE J. Sel. Areas Comm. 13, 6 (Feb.), 1101--1114.

Digital Library

[18]

Guerin, R., Ahmadi, H., and Naghshineh, M. 1991. Equivalent capacity and its application to bandwidth allocation in high-speed networks. IEEE J. Sel. Areas Comm. 9, 7 (Sep.), 968--981.

Digital Library

[19]

Guerin, R. and Gun, L. 1992. A unified approach to bandwidth allocation and access control in fast packet-switched networks. In Proceeding of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM'92). Vol. 1. Florence, Italy, 1--12.

Digital Library

[20]

ITU. 2001. End-user multimedia QoS categories. Tech. rep., ITU-T Recommendation G.1010. (Nov.).

[21]

Jamin, S., Danzig, P., Shenker, S., and Zhang, L. 1997a. A measurement-based admission control algorithm for integrated services packet networks. IEEE/ACM Trans. Netw. 5, 1 (Aug./Sep.), 56--70.

Digital Library

[22]

Jamin, S., Shenker, S. J., and Danzig, P. B. 1997b. Comparison of measurement-based admission control algorithms for controlled-load service. In Proceedings of the Conference on Computer Communications (IEEE INFOCOM '97). Vol. 3. IEEE Computer Society Press, Kobe, Japan, 973--980.

Digital Library

[23]

Perros, H. G. and Elsayed, K. M. 1996. Call admission control schemes: A review. IEEE Comm. Mag. 34, 11 (Nov.), 82--91.

Digital Library

[24]

Sakellari, G., D' Arienzo, M., and Gelenbe, E. 2006. Admission control in self aware networks. In Proceedings of the 49th Annual IEEE Global Telecommunications Conference (GLOBECOM 2006). San Francisco, CA.

[25]

Tse, D. and Grossglauser, M. 1997. Measurement-based call admission control: Analysis and simulation. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '97). Vol. 3. IEEE Computer Society Press, Kobe, Japan, 981--989.

Digital Library

[26]

Warshall, S. 1962. A theorem on Boolean matrices. J. ACM 9, 1 (Jan.), 11--12.

Digital Library

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Çag̃layan U(2021)Performance, Energy Savings and Security: An IntroductionModelling, Analysis, and Simulation of Computer and Telecommunication Systems10.1007/978-3-030-68110-4_1(3-28)Online publication date: 29-Jan-2021
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Index Terms

Admission of QoS aware users in a smart network
1. Networks
  1. Network architectures
  2. Network services

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cover image ACM Transactions on Autonomous and Adaptive Systems

ACM Transactions on Autonomous and Adaptive Systems Volume 3, Issue 1

March 2008

118 pages

ISSN:1556-4665

EISSN:1556-4703

DOI:10.1145/1342171

Issue’s Table of Contents

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 March 2008

Accepted: 01 November 2007

Revised: 01 September 2007

Received: 01 January 2007

Published in TAAS Volume 3, Issue 1

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Çag̃layan U(2021)Performance, Energy Savings and Security: An IntroductionModelling, Analysis, and Simulation of Computer and Telecommunication Systems10.1007/978-3-030-68110-4_1(3-28)Online publication date: 29-Jan-2021
https://doi.org/10.1007/978-3-030-68110-4_1
Liu YYang XCuthbert L(2020)Network Slicing with Spectrum SharingRadio Access Network Slicing and Virtualization for 5G Vertical Industries10.1002/9781119652434.ch8(137-166)Online publication date: 27-Nov-2020
https://doi.org/10.1002/9781119652434.ch8
Soysal MSchmidt E(2019)Machine learning algorithms for accurate flow-based network traffic classificationPerformance Evaluation10.5555/1773005.177317467:6(451-467)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.5555/1773005.1773174
Jaddoa ASakellari GPanaousis ELoukas GSarigiannidis P(2019)Dynamic decision support for resource offloading in heterogeneous Internet of Things environmentsSimulation Modelling Practice and Theory10.1016/j.simpat.2019.102019(102019)Online publication date: Nov-2019
https://doi.org/10.1016/j.simpat.2019.102019
Morfopoulou C(2019)Network routing control with G-networksPerformance Evaluation10.1016/j.peva.2010.12.00868:4(320-329)Online publication date: 1-Jan-2019
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Do T(2019)An initiative for a classified bibliography on G-networksPerformance Evaluation10.1016/j.peva.2010.10.00168:4(385-394)Online publication date: 1-Jan-2019
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Çag̃layan M(2018)Some Current Cybersecurity Research in EuropeSecurity in Computer and Information Sciences10.1007/978-3-319-95189-8_1(1-10)Online publication date: 14-Jul-2018
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Serrano W(2018)The Random Neural Network and Web Search: Survey PaperIntelligent Systems and Applications10.1007/978-3-030-01054-6_51(700-737)Online publication date: 9-Nov-2018
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Domańska JNowak MNowak SCzachórski T(2018)European Cybersecurity Research and the SerIoT ProjectComputer and Information Sciences10.1007/978-3-030-00840-6_19(166-173)Online publication date: 16-Sep-2018
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Abba SLee J(2015)An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor NetworksSensors10.3390/s15082031615:8(20316-20354)Online publication date: 18-Aug-2015
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