Tunable QoS-Aware Network Survivability

Presenter : Yen Fen KaoAdvisor : Yeong Sung Lin

2013 Proceedings IEEE INFOCOM

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 destination node 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.

(, ) = A survivable 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.

23

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 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

Employs two well-know algorithm 1. Edge-Disjoint Shortest Pair(EDSP) algorithm 2. Pseudo-polynomial algorithm scheme

Pseudo-Polynomial Schemes for CO-QAMSC

27

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

Pseudo-Polynomial Schemes for CO-QAMSC

28

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.

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

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

Pseudo-Polynomial Schemes for QoS Aware Survivable Connections

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 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.

37 Agenda

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

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.

Thanks for your attention