Tunable QoS -Aware Network Survivability

1. Tunable QoS-Aware Network Survivability 2013 Proceedings IEEE INFOCOM Presenter : Yen Fen Kao Advisor : Yeong Sung Lin

2. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • Simulation Study • A Network Design Perspective • Conclusions

3. Introduction • Any failure in the network infrastructure may lead to a vast amount of data loss. • Survivability in the network is becoming important.

4. Introduction • Two major classes of recovery schemes： 1. Restoration schemes 2. Protection schemes • This paper adopt the widely used single link failure model. 1. simplicity 2. protecting against a single failure is a common requirement of various standards 3. multiple failures is to supply protection for the first failure and restoration for any subsequent ones

5. Problems • Under the single link failure model, the employment of disjoint paths provides full (100%) protection. • The requirement of fully disjoint paths is often too restrictive and demands excessive redundancy. • A pair of disjoint paths of sufficient quality may not exist. • More flexible survivability concept is called for.

6. Introduction • A previous study introduced the novel concept of tunable survivability. • Provides a quantitative measure to specify the desired level of survivability.

7. Introduction • p-survivable • Is a probability of at least p to have all common links operational during the connection’s lifetime.

8. Introduction • Distinguish between two classes of QoS metrics： 1. bottleneck metrics 2. additive metrics • The important and much more complex class of additive metric was not considered.

9. Example • p-survivable connections combining an additive QoS metric：

10. Introduction • Motivate investigate how to combine the tunable survivability concept with additive QoS guarantees.

11. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • Simulation Study • A Network Design Perspective • Conclusions

12. Model and Problem Formulation • G(V,E) 1. V : the set if nodes 2. E : the set of links 3. N = |V| 4. M = |E| 5. Path : a finite sequence of nodes π =< , , …, > 0 ≤ n ≤ h−1, (, ) ∈ E • A path is simple if all its nodes are distinct.

13. Model and Problem Formulation • Given a source node s ∈ V and a destination node t ∈ V : the set of all simple paths from s to t Each link e ∈ E is associated with a failure probability and positive weight • Assume Each link e ∈ E fails independently Its failure probability is upper-bounded by some value < 1 • Define minimum network success probability =

14. Model and Problem Formulation • Single link failure model considers handling at most one link failure in the network • Classified 1. faulty 2. operational

15. Definition • A source node s ∈ V and a destinationnode t ∈ V, a survivable connection is a pair of paths(, ) ∈ × . • A survivable connection (, ) such that ∩= ∅, we say that (,) is a p-survivable connection if ≥ p. • 1-survivable connection No common links between and .

16. Definition • A network G(V,E) and a (non-empty) path π, its weight W(π) is defined as the sum of the weight of its links. W(π) = • A weight-shortest path between two nodes u, v ∈ V as a path in G(V,E) with minimum weight between u and v.

17. Definition • Define weight 1. minimum of the lengths of two paths => NP-complete 2. worst(highest) among the weights of the two paths => NP-Hard Adopt minimize the aggregate weight of the two paths

18. Definition • A survivable connection (, ), its CO-weight (, ) is defined as the sum of its link weights counting the common links once. (, ) = • Asurvivable connection (, ), its CT-weight(, ) is defined as the sum of its link weights counting the common links twice. (, ) = + • The choice between the two options depends on the Qos metric that the weight represent.

19. Definition • Given： Network G(V,E) A source node s ∈ V and a destination node t ∈ V QoS bound B • CT-Constrained QoS Max-Survivability (CT-CQMS) Problem s.t.(, ) • CO-Constrained QoS Max-Survivability (CO-CQMS) Problem s.t. (, )

20. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • Simulation Study • A Network Design Perspective • Conclusions

21. Definition • A survivable connection (, ), a critical link is a link that is common to both paths and . Accordingly, the set of critical link of a survivable connection is defined as • A source s and a destination t, is the set of all the weight-shortest paths between s and t. • A source node and a destination node , an in-all-weight-shortest-paths link is a link that is common to all paths in . Accordingly, the set of in-all-weight-shortest-paths link is defined as

22. Theorem • For any bound B on the additive end-to-end QoS, an (any)survivable connection (, ) that all its critical links are in-all-weight-shortest-paths links.

24. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • Simulation Study • A Network Design Perspective • Conclusions

25. Establishing QoS Aware p-Survivable Connections • Solution approach is based on a graph transformation. => Restricted Shortest Path(RSP) problem • RSPproblem is the problem of finding a shortest path while obeying an additional constraint.

26. Pseudo-Polynomial Schemes for CO-QAMSC • CO-QoS Aware Max Survivable Connection(CO-QAMSC) Algorithm • Employs two well-know algorithm 1. Edge-Disjoint Shortest Pair(EDSP) algorithm 2. Pseudo-polynomial algorithm scheme

27. Pseudo-Polynomial Schemes for CO-QAMSC • First stage 1. A transformed network(each link have a weight and a success probability) 2. Two types of links simple link：weight = disjoint link：success probability = 0 • Second stage calculates a restricted shortest path

28. Pseudo-Polynomial Schemes for CO-QAMSC • The algorithm finds a pair of path that minimizes = =>max The connection’s survivability level • Third stage Construct the sought pair of paths of survivable connection (, ) out of the link of the RSP solution.

29. Pseudo-Polynomial Schemes for CT-QAMSC • Similar to the CO-QAMSC Algorithmic • Two important changes 1. Transformation of simple links in the new constructed network 2. Stage 0：finds a weight-shortest path in the network G(V,E) by employing a well-known shortest path algorithm

30. Pseudo-Polynomial Schemes for QoS Aware Survivable Connections • A Fully Polynomial Time Approximation Scheme(FPTAS)for solving the PSR problem with an approximation ratio of • The F-CO-QAMSC Algorithm A Fully Polynomial Time Approximation Scheme(FPTAS) for the CO-CQMS problem. Weight of the provided connection is bounded by B Survivability level is at most (1+ε) smaller than the optimal survivability level

31. Example

32. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • Simulation Study • A Network Design Perspective • Conclusions

33. A modest relaxation, of a few percent in the survivability level, is enough to provide significant improvement in terms of delay.

34. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • Simulation Study • A Network Design Perspective • Conclusions

35. Discovering the in-all-weight-shortest-paths links • Finds a weight-shortest pathbyemploying a well-known shortest path algorithm. • Consider a replica of the original network excluding the link of weight-shortest path. • Find in the replica network a weight-shortest path. • If the replica weight is greater than original, then excludeoriginal link belong to the in-all-weight-shortest-paths links set. • If equal, then the excluded original link does not belong to the set. • Repeated for all links of the weight-shortest path of the original.

36. Optimal Links Upgrade Problem • M • The problem can be transformed into an instance of Water-filling problem. • To repeatedly split the upgrade budget among the links of the in-all-weight-shortest-paths link set with the highest failure probability, until eight the budget is exhausted or all the links assume zero failure probability.

37. Agenda • Introduction • Model and Problem Formulation • The Structure of CT Solutions • Establishing QoS Aware p-Survivable Connections • SimulationStudy • A Network Design Perspective • Conclusions

38. Conclusions • Established efficient algorithmic schemes for optimizing the level of survivability while obeying an additive end-to-end QoSconstraint. • Characterized a fundamental property, by which the links that affect the total survivability level of the optimal routing paths belong to a typically small subset. • Demonstrated the advantage of tunable survivability over traditional survivability schemes.

39. Further • The actual deployment of the tunable survivability approach. • This study provides evidence to the profitability of implementing this novel concept, as well as useful insight and building blocks towards the construction of a comprehensive solution.

40. Thanks for your attention