Real-Time Data Analytics in Support of Network Resource Management Protocols

Naghmeh Moradpoor, Gerard Parr, Sally McClean, Bryan Scotney, Gilbert Owusu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Communications Networks Resource Management (RM) functions such as dynamic and static resource usage monitoring, real time resource reservation as well as advance resource reservation have been widely studied in the past few years. Research has been investigating variant techniques for addressing RM problems in different fixed and wireless networks. One of the key observations is that with the increased complexity of these networks, the function of providing real-time OAM&P has resulted in an ever increased network element MIB attribute polling resulting in a data mountain. The key issue is to extract intelligence from this data using data analytical tools in an efficient manner if it is to have any impact on optimising real-time network resource utilisation as a function of demand. This paper reviews some of the recent techniques conducted in RM for different domains. We discuss data management (DM) in telecommunications and try to depict its role to support our real-time data analytics within the OAM&P functions. The main purpose of this paper is to investigate RM components in groups of networks (ATM, MPLS, Wireless, EPONs) and indicate recent solutions for each group.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages6
Publication statusPublished - Jun 2009
EventThe 10th Annual Conference on teh Convergence of Telecommunications, Networking & Broadcasting - Liverpool
Duration: 1 Jun 2009 → …

Conference

ConferenceThe 10th Annual Conference on teh Convergence of Telecommunications, Networking & Broadcasting
Period1/06/09 → …

Fingerprint

Network protocols
Asynchronous transfer mode
Information management
Telecommunication networks
Telecommunication
Wireless networks
Monitoring

Keywords

  • Resource Management
  • Data Mining
  • Optimisation
  • Next Generation Networks

Cite this

Moradpoor, N., Parr, G., McClean, S., Scotney, B., & Owusu, G. (2009). Real-Time Data Analytics in Support of Network Resource Management Protocols. In Unknown Host Publication
Moradpoor, Naghmeh ; Parr, Gerard ; McClean, Sally ; Scotney, Bryan ; Owusu, Gilbert. / Real-Time Data Analytics in Support of Network Resource Management Protocols. Unknown Host Publication. 2009.
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abstract = "Communications Networks Resource Management (RM) functions such as dynamic and static resource usage monitoring, real time resource reservation as well as advance resource reservation have been widely studied in the past few years. Research has been investigating variant techniques for addressing RM problems in different fixed and wireless networks. One of the key observations is that with the increased complexity of these networks, the function of providing real-time OAM&P has resulted in an ever increased network element MIB attribute polling resulting in a data mountain. The key issue is to extract intelligence from this data using data analytical tools in an efficient manner if it is to have any impact on optimising real-time network resource utilisation as a function of demand. This paper reviews some of the recent techniques conducted in RM for different domains. We discuss data management (DM) in telecommunications and try to depict its role to support our real-time data analytics within the OAM&P functions. The main purpose of this paper is to investigate RM components in groups of networks (ATM, MPLS, Wireless, EPONs) and indicate recent solutions for each group.",
keywords = "Resource Management, Data Mining, Optimisation, Next Generation Networks",
author = "Naghmeh Moradpoor and Gerard Parr and Sally McClean and Bryan Scotney and Gilbert Owusu",
note = "Reference text: [1] J. Evans, C. Filsfils, M. Kaufmann,”Deploying IP and MPLS QoS for Multiservice Networks: Theory and Practice”, 2007. [2] H. A. Taha, “Operations Research: an Introduction”, 7th Edition, Maxwell MacMillan, 2003. [3] K. Sven, G. Conti, J. Grizzard, J. Gribschaw and H. Owen, “Real-Time and Forensic Network Data Analysis Using Animated and Coordinated Visualization”, IEEE Workshop on Information assurance, 2005. [4] D.J. Mitzel, D. Estrin, S. Shenker, L. Zhang, “An Architectural Comparison of ST-2 and RSVP, IEEE Proc-Communications, 1994. [5] J. Zheng, “Efficient bandwidth allocation algorithm for Ethernet passive optical networks”, IEEE Proc-Communications, 2006. [6] J. Qiu, “An Adaptive Dynamic Bandwidth Allocation Algorithm for WiMAX/IEEE802.16d Systems”, 2007. [7] D. Wang, G. Li, “Efficient Distributed Bandwidth Management for MPLS Fast Reroute”, IEEE/ACM Transactions, 2008. [8] M. Li, K. Sandrasegaran, “Network Management Challenges for NGN”, IEEE Conferences, 2005. [9] K. Krishnasamy, N. Palanisamy, “Bandwidth Allocation Scheme for Multimedia Mobile Networks Using Optimization Techniques”, IEEE Conference, 2006. [10] D. Sanda, D. Radu, “Bandwidth Management in MPLS Networks”, 2001. [11] D. Awduche, L. Berger, D. Gan, T. Li, V. Srinivasan, “RSVP-TE: Extensions to RSVP for LSP Tunnels, RFC3209”, IETF, 2001. [12] P. Pan, G. Swallow, A. Atlas, “Fast Reroute Extensions to RSVP-TE for LSP Tunnels RFC 4090”, IETF, 2005. [13] C. Assi, Y. Ye, S. Dixit, M. Ali, “Dynamic bandwidth allocation for quality-of-service over Ethernet PONs“, IEEE Journal, 2003. [14] V. Rakocevica, J. Griffithsa, G. Copeb, “Performance Analysis of Bandwidth Allocation Schemes in Multiservice IP Networks using Utility Functions”, 2002. [15] D.D. Nauck, M. Spott, B. Azvine, ‘Fuzzy Methods for Automated Intelligent Data Analysis’, IEEE Conference, 2004. [16] M. Srinivas, M. Patnaik, “Adaptive probabilities of crossover and Mutation in Genetic Algorithms”, IEEE Transactions, 1994. [17] B.P.V. Kumar and P. Venkataram, “An LP-based Admission Control Using Artificial Neural Networks for Integrated Services in Mobile Networks”, Springer Netherlands, 2002. [18] M. Sundarambal, B.J. Chithara, P. Anbalagan, “Meta-Heuristic Techniques for Bandwidth Optimization through Dynamic Routing in ATM networks “, Medwell Journals, 2008. [19] W. Reinhardt, “Advance Resource Reservation and its Impact on Reservation Protocols”, 2008. [20] K.G.Knightson, “Basic NGN Architecture and Principles”, 2005, http://www.itu.int [21] E. Rosen, A. Viswanathan, R. Callon, “Multiprotocol Label Switching Architecture (MPLS), RFC 3031“, IETF, 2001. [22] R. Cole, D. Shur, C. Villamizar, “IP over ATM, RFC 1932”, IETF, 1996. [23] A. Mankin, F. Baker, B. Braden, S. Bradner, M. O`Dell, A. Romanow, A. Weinrib, L. Zhang, “Resource ReSerVation Protocol (RSVP), RFC 2208”, IETF, 1997. [24] K. Nichols, S. Blake, F. Baker, D. Black, “Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers, RFC 2474”, IETF, 1998. [25] M. Srinivas, M. Patnaik Lalit, “Genetic Algorithms: A survey”, 1994. [26] M. Resende, P. Pardalos, “Optimization in Telecommunications“,2006.",
year = "2009",
month = "6",
language = "English",
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Moradpoor, N, Parr, G, McClean, S, Scotney, B & Owusu, G 2009, Real-Time Data Analytics in Support of Network Resource Management Protocols. in Unknown Host Publication. The 10th Annual Conference on teh Convergence of Telecommunications, Networking & Broadcasting, 1/06/09.

Real-Time Data Analytics in Support of Network Resource Management Protocols. / Moradpoor, Naghmeh; Parr, Gerard; McClean, Sally; Scotney, Bryan; Owusu, Gilbert.

Unknown Host Publication. 2009.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Real-Time Data Analytics in Support of Network Resource Management Protocols

AU - Moradpoor, Naghmeh

AU - Parr, Gerard

AU - McClean, Sally

AU - Scotney, Bryan

AU - Owusu, Gilbert

N1 - Reference text: [1] J. Evans, C. Filsfils, M. Kaufmann,”Deploying IP and MPLS QoS for Multiservice Networks: Theory and Practice”, 2007. [2] H. A. Taha, “Operations Research: an Introduction”, 7th Edition, Maxwell MacMillan, 2003. [3] K. Sven, G. Conti, J. Grizzard, J. Gribschaw and H. Owen, “Real-Time and Forensic Network Data Analysis Using Animated and Coordinated Visualization”, IEEE Workshop on Information assurance, 2005. [4] D.J. Mitzel, D. Estrin, S. Shenker, L. Zhang, “An Architectural Comparison of ST-2 and RSVP, IEEE Proc-Communications, 1994. [5] J. Zheng, “Efficient bandwidth allocation algorithm for Ethernet passive optical networks”, IEEE Proc-Communications, 2006. [6] J. Qiu, “An Adaptive Dynamic Bandwidth Allocation Algorithm for WiMAX/IEEE802.16d Systems”, 2007. [7] D. Wang, G. Li, “Efficient Distributed Bandwidth Management for MPLS Fast Reroute”, IEEE/ACM Transactions, 2008. [8] M. Li, K. Sandrasegaran, “Network Management Challenges for NGN”, IEEE Conferences, 2005. [9] K. Krishnasamy, N. Palanisamy, “Bandwidth Allocation Scheme for Multimedia Mobile Networks Using Optimization Techniques”, IEEE Conference, 2006. [10] D. Sanda, D. Radu, “Bandwidth Management in MPLS Networks”, 2001. [11] D. Awduche, L. Berger, D. Gan, T. Li, V. Srinivasan, “RSVP-TE: Extensions to RSVP for LSP Tunnels, RFC3209”, IETF, 2001. [12] P. Pan, G. Swallow, A. Atlas, “Fast Reroute Extensions to RSVP-TE for LSP Tunnels RFC 4090”, IETF, 2005. [13] C. Assi, Y. Ye, S. Dixit, M. Ali, “Dynamic bandwidth allocation for quality-of-service over Ethernet PONs“, IEEE Journal, 2003. [14] V. Rakocevica, J. Griffithsa, G. Copeb, “Performance Analysis of Bandwidth Allocation Schemes in Multiservice IP Networks using Utility Functions”, 2002. [15] D.D. Nauck, M. Spott, B. Azvine, ‘Fuzzy Methods for Automated Intelligent Data Analysis’, IEEE Conference, 2004. [16] M. Srinivas, M. Patnaik, “Adaptive probabilities of crossover and Mutation in Genetic Algorithms”, IEEE Transactions, 1994. [17] B.P.V. Kumar and P. Venkataram, “An LP-based Admission Control Using Artificial Neural Networks for Integrated Services in Mobile Networks”, Springer Netherlands, 2002. [18] M. Sundarambal, B.J. Chithara, P. Anbalagan, “Meta-Heuristic Techniques for Bandwidth Optimization through Dynamic Routing in ATM networks “, Medwell Journals, 2008. [19] W. Reinhardt, “Advance Resource Reservation and its Impact on Reservation Protocols”, 2008. [20] K.G.Knightson, “Basic NGN Architecture and Principles”, 2005, http://www.itu.int [21] E. Rosen, A. Viswanathan, R. Callon, “Multiprotocol Label Switching Architecture (MPLS), RFC 3031“, IETF, 2001. [22] R. Cole, D. Shur, C. Villamizar, “IP over ATM, RFC 1932”, IETF, 1996. [23] A. Mankin, F. Baker, B. Braden, S. Bradner, M. O`Dell, A. Romanow, A. Weinrib, L. Zhang, “Resource ReSerVation Protocol (RSVP), RFC 2208”, IETF, 1997. [24] K. Nichols, S. Blake, F. Baker, D. Black, “Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers, RFC 2474”, IETF, 1998. [25] M. Srinivas, M. Patnaik Lalit, “Genetic Algorithms: A survey”, 1994. [26] M. Resende, P. Pardalos, “Optimization in Telecommunications“,2006.

PY - 2009/6

Y1 - 2009/6

N2 - Communications Networks Resource Management (RM) functions such as dynamic and static resource usage monitoring, real time resource reservation as well as advance resource reservation have been widely studied in the past few years. Research has been investigating variant techniques for addressing RM problems in different fixed and wireless networks. One of the key observations is that with the increased complexity of these networks, the function of providing real-time OAM&P has resulted in an ever increased network element MIB attribute polling resulting in a data mountain. The key issue is to extract intelligence from this data using data analytical tools in an efficient manner if it is to have any impact on optimising real-time network resource utilisation as a function of demand. This paper reviews some of the recent techniques conducted in RM for different domains. We discuss data management (DM) in telecommunications and try to depict its role to support our real-time data analytics within the OAM&P functions. The main purpose of this paper is to investigate RM components in groups of networks (ATM, MPLS, Wireless, EPONs) and indicate recent solutions for each group.

AB - Communications Networks Resource Management (RM) functions such as dynamic and static resource usage monitoring, real time resource reservation as well as advance resource reservation have been widely studied in the past few years. Research has been investigating variant techniques for addressing RM problems in different fixed and wireless networks. One of the key observations is that with the increased complexity of these networks, the function of providing real-time OAM&P has resulted in an ever increased network element MIB attribute polling resulting in a data mountain. The key issue is to extract intelligence from this data using data analytical tools in an efficient manner if it is to have any impact on optimising real-time network resource utilisation as a function of demand. This paper reviews some of the recent techniques conducted in RM for different domains. We discuss data management (DM) in telecommunications and try to depict its role to support our real-time data analytics within the OAM&P functions. The main purpose of this paper is to investigate RM components in groups of networks (ATM, MPLS, Wireless, EPONs) and indicate recent solutions for each group.

KW - Resource Management

KW - Data Mining

KW - Optimisation

KW - Next Generation Networks

M3 - Conference contribution

BT - Unknown Host Publication

ER -