1 Quality of resilience as a network reliability characterization tool Cholda, P.; Tapolcai, J.; Cinkler, T.; Wajda, K.; Jajszczyk, A.; Network, IEEE Network,

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Presentation transcript:

1 Quality of resilience as a network reliability characterization tool Cholda, P.; Tapolcai, J.; Cinkler, T.; Wajda, K.; Jajszczyk, A.; Network, IEEE Network, IEEE 指導教授:童曉儒 老師 報告人 :林祐沁 學生 日期 : 2009/06/08

2 Outline Introduction Relationship between QoS and QoR Quality of Resilience Numerical Example: The Impact of Protection Mechanisms on QoR Conclusions

3 Introduction Interruption could cause large loss of data the networks are equipped with relevant mechanisms enabling survival under network failures. A sequence of operations is necessary to perform this task: fault detection, fault localization, fault notification, and recovery switching.

4 Introduction Many measures have been proposed for different environments.

5 Introduction

6

7 Comprehensive characterization of various recovery methods implemented in multilayer networks. Propose advanced QoS definitions, which include service resilience measures called quality of resilience (QoR).

8 Relationship between QoS and QoR QoS is the umbrella representing the measurable (objective) requirements of the users regarding the service. bit error rate (BER), delay, packet loss probability, available bandwidth, traffic load, and throughput.

9 Relationship between QoS and QoR In SLAs the long-term and short-term quality characteristics can be defined. short-term quality metrics : related to the instant perceived quality of the service provided to the user. long-term measure : the overall service quality during the whole length of service operation.

10 Relationship between QoS and QoR

11 Relationship between QoS and QoR Metrics cannot be distinguished just from quality degradation. An end user recognizes increased delay or packet loss in the service layer leading to a certain level of TCP throughput degradation. Those impairments might be either network congestion due to uncontrolled traffic variability, or even a hardware failure.

12 Relationship between QoS and QoR

13 Relationship between QoS and QoR The measurement or interpretation can be performed by dividing the whole observation interval.

14 Quality of Resilience QoR metric to compare all types of recovery strategies.  It is a fractile (quantile) representation of downtimes over the long run. characterization purposes to report failure intensities and recovery times for management purposes. provider-oriented approach to select recovery strategies on the basis of simulated QoR histograms.

15 Quality of Resilience

16 Quality of Resilience QoR encompasses all of fllows: Steady-state availability and unavailability. Mean time to recovery. Mean time to failure. T: the length of the downtime

17 Quality of Resilience The probability of uninterrupted service The availability of the service is related to the threshold value of time α Mean time to recovery Mean time to failure

18 Numerical Example: The Impact of Protection Mechanisms on QoR Without recovery, the probability of losing the service is The dedicated protection of single link/node faultsrestoration in less than 20 ms.

19 Numerical Example: The Impact of Protection Mechanisms on QoR Shared path protection method single link faults with the usage of the Dijkstra algorithm. integer linear programming (ILP) to ensure the optimality of the solution

20 Numerical Example: The Impact of Protection Mechanisms on QoR Shared segment protection first the working path is routed on the shortest path. the second step a disjoint shared protection route is selected with a heuristic.

21 Numerical Example: The Impact of Protection Mechanisms on QoR Shared protection scenarios providing resilience against dual faults. dual fault with the Dijkstra algorithm

22 Numerical Example: The Impact of Protection Mechanisms on QoR Mean time to recovery and some conditional fractile values are given in the description of the recovery scheme. Fractiles can describe resilience more precisely Shared segment protection of single link faults with recovery time constraints, MTTR = 3 min, t 25%|>0 = 50 ms, t 50%|>0 = 60 ms, t 75%|>0 =70 ms Dual fault with the Dijkstra algorithm, MTTR = 90 ms, t 25%|>0 = 60 ms, t 50%|>0 = 80 ms, t 75%|>0 = 100 ms. hreshold value like 50 ms, the standard required recovery time for SDH networks

23 Conclusions Avoid : choosing an improper recovery method not adequate for user or application quality requirements. Dealing with resilience in too narrow a scope based on only averaged metrics to describe a multidimensional quality problem. Adopting too simple resilience agreements with customers that might lead to liability problems.