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

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

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

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 4

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. 5

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

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.

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

Model and Problem Formulation 12

13 Model and Problem Formulation

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

16 Definition

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

19 Definition

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

21 Definition

22 Theorem

23

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

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

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

27 Pseudo-Polynomial Schemes for CO-QAMSC

28 Pseudo-Polynomial Schemes for CO-QAMSC

29  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 Pseudo-Polynomial Schemes for CT-QAMSC

30 Pseudo-Polynomial Schemes for QoS Aware Survivable Connections

31 Example

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

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

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

35 Discovering the in-all-weight-shortest-paths links  Finds a weight-shortest path by employing 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 exclude original 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.

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

38 Conclusions  Established efficient algorithmic schemes for optimizing the level of survivability while obeying an additive end-to-end QoS constraint.  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.

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