Dynamic Topology Configuration in Service Overlay Networks: A Study of Reconfiguration Policies

1. Dynamic Topology Configuration in Service Overlay Networks: A Study of Reconfiguration Policies Authors: Jinliang Fan and Mostafa H. Ammar Presented by: Srinivasan Seetharaman Networking and Telecommunications Group College of Computing, Georgia Tech

2. Introduction • Overlay Networks • Native infrastructure of Internet has become resistant to fundamental changes • Overlay networks can provide the desirable flexibility and control • Example applications • Application layer multicast • Testbeds for new technologies • Circumventing BGP faults and constraints

3. Service Overlay Networks

4. Dynamic Topology Configuration • Topology configurability in small time scales • a key feature of overlay networks • Our contributions: • Optimal topology reconfiguration policies: properties and approximation • evidence for the advantage of overlay networks due to their configurability

5. Choosing Overlay Topologies Underlying network + Application’s communication requirement Possible overlay topologies

6. Main question • When and how should the overlay topology be reconfigured as the traffic patterns change?

7. Reconfiguration Cost • Topology Reconfiguration has a cost • Overhead of establishing and tearing down overlay links • Disruption to ongoing flows

8. Costs Involved • Occupancy cost: traffic operation cost • Reconfiguration cost: control and rerouting overhead • Protocol dependent • Estimated with the number of changed overlay links • Overall cost • Weighting factorβis protocol specific and application specific

9. A Reconfiguration Policy • An overlay topology reconfiguration policy is • The sequence of overlay topologies used in response to changing traffic over time

10. Policy Optimization • Optimization objective: minimizing long-term overall cost

11. Two Extreme Policies • Never Change Policy • Optimal if Reconfiguration Cost is very high • Always Change Policy • Optimal if Reconfiguration Cost is zero

12. General Approach • Modeling the problem of finding optimal reconfiguration policy as Markov Decision Process • Small number of nodes and Markovian process of comm. patterns • Solving using Howard’s policy iteration method • Observing properties of optimal policies • Developing approximation policies that can be also used for large, non-Markovian systems

13. Traffic and Overlay Topology • Traffic changes over time • X(t) traffic matrix at time t • From a set of communication patterns {C1, … , Cs} • Feasible overlay topologies • From a set {T1, … , Tr} • Fixed number of nodes and degree bounded • State: <Traffic, Topology>

14. Properties of Optimal Policies:A. Reconfiguration Chains

15. Properties of Optimal Policies:B. Threshold Behavior Not-aggressive Aggressive

16. Properties of Optimal Policies:C. Internal Structure • Comm. patterns sharing thesame topology form a cluster • Most clusters do not overlap • Global factors affect # of clusters • Weight of reconfiguration cost  • Average transition rate  • Local factors affect whether two comm. patterns belong to the same cluster • imbalance of occupancy time • level of coupling • similarity

17. Approximating Optimal Policies • Mimic optimal policies and generate topologies in polynomial time • Use different types of approximation policies for scenarios with different range of β (the weight of reconfiguration cost) • β in lower extreme area. Always-Change Policy • β in higher extreme area. Never-Change Policy • β in middle area. Cluster-Based Policy (Group the communication patterns based on clusters andidentify 1 topology to be used by cluster members)

18. Required information for constructing clusters • Percentage of long-term average occupancy time at each communication pattern • Long-term average number of transitions between every pair of communication patterns per unit time

19. Performance Evaluation • In small overlay network with 5 overlay nodes

20. Performance Evaluation (contd.) • In large overlay network with 40 overlay nodes Markovian Non-Markovian

21. Effect of Degree Bound • Irrespective of degree we use • dynamic reconfiguration provides benefit. • dynamic reconfiguration is best when the reconfiguration policy cost is low. • Service provider may need to decide on a tradeoff between the complexity of dynamic reconfiguration and cost of high degree bound.

22. Concluding Remarks • Topology configurability is one of the important capabilities provided • Investigated a framework for determining reconfiguration policies • Careful reconfiguration can maintain overlay performance without increasing cost

23. Questions? • Please contact: • Jinliang jlfan@cc.gatech.edu • Mostafa ammar@cc.gatech.edu Thank you!