Title: Policy Analysis for Quality of Service Management
Author: Marinos Charalambides
e-mail: M.Charalambides@surrey.ac.uk
Partner: UniS
Supervisor: George Pavlou
Committee:
Year of start: 2003
Year of end: 2008
Funding institution: Centre for Communication Systems Research, University of Surrey

The rapid evolution of the Internet, the increasing complexities and heterogeneity of modern networking technology, and the increase in the number of resources to be managed, pose a significant challenge to network management models. Policy-based Network Management (PBNM) is a promising solution for these demands, providing the means by which the administration process can be simplified and largely automated in a flexible manner. The policy-based approach can be used to manage different aspects of a network commonly known as policy disciplines. The main interest in network policies is to manage and control the QoS experienced by networked applications and users, by configuring network elements using specific rules that define which traffic should be treated differently in the network, and how so.
Although extensive work has been done in developing policy specification languages, protocols and architectures to support policy-based management, little attention has been devoted to the area of policy analysis. Policy analysis is considered to be an essential component of modern PBNM solutions and comprises two functionalities: conflict detection and resolution.
In a real networking scenario, multiple policies will apply to network elements in order to support the requirements of different applications and users. Furthermore, the network’s shared resources are composed of several elements with varying capabilities and interfaces. Therefore, there is an apparent need for checking policy consistency prior to deployment, where a conflict detection process can identify any omissions, errors or conflicting requirements of the administrators specifying the policies. In the case of a conflict it is necessary to apply resolution techniques to either prevent a policy from being deployed or suggest ways in which the specification should change to guarantee policy integrity.
As such, the objectives of this thesis are to identify and classify policy conflicts related to the area of QoS management, and also define techniques and methodologies for their detection and resolution. More specifically, we investigate policy conflicts in the context of service and resource management in IP DiffServ Networks, and develop tools that provide support for both static and dynamic conflict detection as well as automated resolution. This work makes use of Event Calculus, a logic-based formalism, which apart from the representation of policies and managed components it provides the system with a certain degree of reasoning ability.

1. A.M. Hadjiantonis, M. Charalambides, G. Pavlou, “An Adaptive Service Management Framework for Wireless Networks”, published in IEEE Vehicular Technology Magazine, Special Issue on Policy-based Management for Wireless Multimedia Services, IEEE, Vol. 2, Iss. 3 , p.6-13, Sept 2007.
2. A. Hadjiantonis, M. Charalambides, G. Pavlou, “A Policy-based Approach for Managing Ubiquitous Networks in Urban Spaces,” Proceedings of the IEEE International Conference on Communications (ICC 2007), Glasgow, UK, June 2007.
3. J. Loyola, J. Serrat, M. Charalambides, P. Flegkas, G. Pavlou, “A Methodological Approach toward the Refinement Problem in Policy-Based Management Systems,” IEEE Communications Magazine, Topics in Network and Service Management, Vol. 44, No. 10, October 2006.
4. J. Loyola, J. Serrat, M. Charalambides, P. Flegkas, G. Pavlou, “A Functional Environment Solution for Goal-oriented Policy Refinement,” Proceedings of the 7th IEEE Workshop on Policies for Distributed Systems and Networks (Policy 2006), Ontario, Canada, June 2006.
5. M. Charalambides, P. Flegkas, G. Pavlou, J. Loyola, A. Bandara, E. Lupu, A. Russo, N. Dulay, M. Sloman, “Dynamic Policy Analysis and Conflict Resolution for DiffServ Quality of Service Management,” Proceedings of IEEE/IFIP Network Operations and Management Symposium (NOMS 2006), Vancouver, Canada, April 2006.
6. J. Loyola, J. Serrat, M. Charalambides, P. Flegkas, G. Pavlou, “GOREMOCH: A Distributed Goal-oriented Policy Refinement Environment,” Proceedings of IEEE/IFIP Network Operations and Management Symposium (NOMS 2006), Vancouver, Canada, April 2006.
7. A. Bandara, E. Lupu, A. Russo, N. Dulay, M. Sloman, P. Flegkas, M. Charalambides, G. Pavlou, “Policy Refinement for DiffServ Quality of Service Management,” Poster: Proceedings 13th HP Openview University Association Workshop, Portugal, July 2005.
8. A. Bandara, E. Lupu, A. Russo, N. Dulay, M. Sloman, P. Flegkas, M. Charalambides, G. Pavlou, “Policy Refinement for IP Differentiated Services Quality of Service Management,” IEEE e-Transactions on Network and Service Management, 3(2), 2006.
9. M. Charalambides, P. Flegkas, G. Pavlou, A. Bandara, E. Lupu, A. Russo, N. Dulay, M. Sloman, J. Loyola, “Policy Conflict Analysis for Quality of Service Management,” Proceedings of the 6th IEEE Workshop on Policies for Networks and Distributed Systems (Policy 2005), Stockholm, Sweden, 2005.
10. J. Loyola, J. Serrat, M. Charalambides, P. Flegkas, G. Pavlou, A. Lafuente, “Using Linear Temporal Model Chacking for Goal-oriented Policy Refinement Frameworks,” Proceedings 6th IEEE Workshop on Policies for Distributed Systems and Networks (Policy 2005), Stockholm, Sweden, June 2005.
11. A. Bandara, E. Lupu, A. Russo, N. Dulay, M. Sloman, P. Flegkas, M. Charalambides, G. Pavlou, “Policy Refinement for DiffServ Quality of Service Management,” Proceedings of the 9th IEEE/IFIP Integrated Management Symposium (IM 2005), Nice, France, 2005.