Efficient agent-based selection of DiffServ SLAs over MPLS networks Thanasis G. Papaioannou a,b, Stelios Sartzetakis a, and George D. Stamoulis a,b presented by Vasilios Siris a SPIE International Symposium on Information Technologies: Internet Performance and Control, Boston, U.S.A., November 2000 a Institute of Computer Science (ICS), Foundation for Research & Technology – Hellas (FORTH) P.O. Box 1385, GR , Heraklion, Crete, Greece b Department of Computer Science, University of Crete, Heraklion, Greece

2 Outline l Introduction and problem definition l Our contribution l Overview of the architecture l The SLS selection process l Implementation issues l Theoretical and experimental assessment of the economic efficiency achieved. l Conclusions – future work

3 Introduction and Problem Definition l QoS provision in Internet is (and will be) necessary. l Many QoS protocols and mechanisms have been proposed. è SLA negotiation algorithms have to be defined properly, in order for ISPs to sell such contracts that: n satisfy user needs, n improve network efficiency.

4 Our Contribution l Development and assessment of an architecture for per-flow SLA negotiation, provision and control deployment in a DiffServ over MPLS network domain. l Development and assessment of an efficient SLS selection process. l Implementation of the whole system in an experimental testbed.

5 Overview of the Architecture Policy Server User Agent SLS negotiation LSP QoS requests DiffServ over MPLS network domain Policy Directory Information Directory

6 QoS Issues l Each QoS class has n the same performance characteristics over all paths, n a certain non-compliance risk r. l Non-compliance risk is defined as an a priori upper bound on the percentage of traffic that will not be treated in accordance to the SLS. n Computable by the network provider. n Understandable for the end-users. l User QoS requirements: 1.maximum acceptable non-compliance risk. 2.minimum acceptable QoS class.

7 The Efficient SLS Selection Process l The user application places a QoS request. l This request reaches the Policy Server, which discovers the feasible SLSs [x = (h, ρ, β, QoS class, r)] and their associated expected charge. l The User Agent selects the SLS x that maximizes the net benefit of the user, i.e.

8 Charging by the Most Congested Link n s i, t i characterize the operating point of a QoS class i. n p i is the price per unit of effective usage in a QoS class i. n T is the service duration. l This scheme is fair and provides users with the right incentives for resource usage. l The PS computes the expected charge according to [Courcoubetis-Siris]: è simple bound of effective bandwidth

9 Optimization of Traffic Parameters l For a given peak rate h (or a shaping delay) there is an indifference curve of (ρ, β) pairs for which all the inserted traffic is conformant. l For charge minimization  Minimize H(t) over this curve. l Assumption: PS offers only one optimized contract x, per QoS class. Negotiation now simplified: selection of x reduces to selection of QoS class and r.

10 The User Utility Function l The user utility for a SLS x: n U(QoS DF ) is a normalized user utility function of the QoS class. n W(x) expresses the willingness to pay of a user for the QoS class, when for the highest QoS class he is willing to pay W max. n r user is the upper bound of the noncompliance risk that the user can accept, while r netw is the noncompliance risk offered by the network. n The function f expresses the user satisfaction for low values of r netw relatively to r user.

11 A Typical Function U(QoS DF ) Minimum Acceptable QoS class

12 A Reasonable Function  (r user, r netw )

13 Distribution and Exchange of Information l Each component stores information for which it has the proper incentive.

14 Efficiency of Architecture l Performs traffic categorization in QoS classes, rather than CAC. l In the network ingress n Clear and effective SLS negotiation interface. n Per flow traffic classification, control of compliance with the SLSs, and DS assignment to the packets. l Processing of QoS requests and state storage only by the PS. l Simple expression of user QoS requirements. l Low computational overhead and minor additions to the existing infrastructure. l Scaleable architecture in large administrative domain, using multiple PS instances.

15 Economic Efficiency l Each user performs individual optimization. n Is incentive compatibility maintained when users employ this negotiation process for SLS selection? I.e. is social welfare also promoted? l Experiments: Computation of social welfare when employing: 1.our negotiation approach. 2.equal sharing of the same total amount of resources. l Results: social welfare always better under our approach.

16 Conclusions – Future Work l Defined and implemented n an architecture for control and categorization of the inserted traffic in a DiffServ over MPLS network domain. n an efficient SLS selection process, providing the right incentives to users. l The whole system can serve as n a framework for the employment of different resource allocation and charging policies for the improvement of the overall efficiency of the network. l Directions for future work: Extend the system n for negotiation of aggregate SLSs between DiffServ domains. n for end-to-end SLA deployment across multiple DiffServ domains.

17 Support Slides

18 Experimental Results è Our approach is better for all the charging curves and for all the amounts that the users are willing to pay.

19 DiffServ over MPLS Network

20 Formulae in Experiments