high availability survivable networks

1. high availability survivable networks High Availability Survivable Networks:When is Reducing MTTR Better than Adding Protection Capacity? Wayne D. Grover, Anthony Sack9 October 2007 Presented at: 7-10 October 2007 La Rochelle, France

2. Segue….back to DRCN 2005 Beautiful Ischia. ..the closing Panel Discussion. Question for Dr. Grover: (paraphrasing) “In a network that is already designed for single failure restorability, to get yet higher availability of services, would you think it is better to add still more spare capacity to increase the dual-failure restorability or to invest at that point in MTRR reduction to enhance availability?” GOOD QUESTION ! …and it lead to this study..

3. Reduce physical MTTR values for network spans • physical repairs will happen faster • Time spent in an overlapping dual failure repair state will go down as MTTR-2 • As MTTR ->0 there are no dual failures Why this question is so insightful… To minimize the impact of dual-failure events, we can: Increase the network restorability to dual span failures • By adding more spare capacity • fewer dual-failure pairs will be outage causing • R2 = 1 means a triple failure will be needed to cause outage! Which is best approach? Is there an optimal investment strategy?

4. In a survivable network, MTTR takes on new importance… • Key point is that in an R1=1 survivable network, outage requires two failures which interact in the network (restoration-wise) with repair processes that overlap in time • Otherwise the two failures are simply time-successive single failures. • This means that: In a survivable network, unavailability drops as the square of the MTTR !

5. Illustrating the principle Decreasing time to repair No risk of outage(R1=1) TTR_Failure_2 TTR_Failure_1 R2<1: risk of outage. Duration proportional to repair overlap time. Reduces as Increasing time to repair

6. Study mandate and design • Explore the trade-off between availability improvement through R2 enhancement and MTTR reduction. Framework: Total Availability Investment 100% to Physical MTTR Reduction 100% to Dual-failure Restorability (R2) • Interesting because the response of both variables to increasing investment is not linear. What is the most cost-effective strategy for combined investment in capacity additions and repair time improvements to maximize availability?

7. Some Terminology • “R1” is the level of single-failure restorability (range 0 to 1) • “R2” is the level of dual-failure restorability (range 0 to 1 as well) • Examples: • R1 = 1 indicates a network fully restorable to all single failures; • R2 = 0.60 means that 60% of failed working capacity units (or service paths) are restorable to dual failures, on average.

8. Typical capacity cost profile of enhancing R2 • Any network designed for100% R1 will always havea non-zero R2 level as well. • This is true even if the R1network design is optimal. • R2 vs. cost curve thenasymptotically approachesunity – always a diminishingreturn to further capacity investment. • This characteristic curve shape is well-known in the literature. Exact shapes for this curve have been found for different networks in, for example, the Ph.D. thesis by Clouquer

9. Properties of MTTR versus expenditure • Shape of the MTTR vs. costcurve is much less certain, but a plausible parametricmodel seems defensible. • For example, initialinvestments lead to largeMTTR reductions, withdiminishing returns thereafter. • Conceivably,however, this curve could alsobe convex – with initial investments leading to only small reductions, and larger investments required for larger changes. • Both scenarios will be tested in our experimental calculations.

10. (One failureon the path) (Both failures on the path) Number of dual-failure scenarios that may cause service path outage Probability of any dual-failure event actually occurring dual-span failure restorability of the network Theoretical model development • Consider the availability of an individualreference path in an R1 survivable network:(for conceptual investigation, all spans taken as identical;S: number of spans in the network, N: number of spans on the path) • This expression excludes contributions due to triple (or higher-order) independent failure scenarios.

11. Approximation:(where λ is the failure rate) & Also: Algebraically simplify “number of scenarios” term from before Switch to an unavailability orientation Relation of unavailability to MTTR • We can now express the span unavailability in terms of MTTR: Well-known expression:

12. Unavailability as a function of MTTR and R2 • We now have the operative expression that relates unavailability to both MTTR and R2: • Note that unavailability responds in a linear way to R2, but to the square of the MTTR or failure rate (λ). Could availability improvements be most optimally gained through MTTR improvements or some type of combined strategy with R2 enhancement?

13. MTTR and R2 as functions of cost • To study the economic tradeoff, we define MTTR and R2 as functions of cost: • If Cm + Cr is a constant total budget amount, then an optimum split of total investment must exist which minimizes Upath. What is this optimum split for each of the two MTTR characteristic curve shapes postulated earlier?

14. N, S, λ Experimental calculations • For experimental calculations,we set a numerical value of 100“arbitrary cost units” to be dividedbetween MTTR and R2.(i.e. total investment remains constant,only the allocation changes) • Data points from the characteristic curves for both variables were used in the equation just presented to generate new curves for the unavailability of a typical reference path. • Test one: concave MTTRTest two: convex MTTR Other assumed parameters:N = 6 (length of the reference path)S = 20 (number of spans in the network)λ = 0.0005 (failure rate per span)

15. Average R2(i,j) Achieved % of Total Budget Spent on R2 Enhancement Experimental R2 curve (both tests)

16. MTTR (hours) % of Total Budget Spent on MTTR Reduction Experimental MTTR curve – concave (test one)

17. Region 3 Region 2 Reference Path Unavailability Region 1 % of Total Budget Spent on MTTR Reduction(Balance goes to R2 Enhancement) Test one result

18. Test one: discussion • Three distinct regions evident. • In Region 1 Availability greatlybenefits from relatively easilyobtained initial reductions in MTTR. • In Region 3 MTTR reduction isa matter of diminishing returns. It would have been better to add more capacity with the same money, to enhance R2. • In Region 2, the overall availability is lowest and not very sensitive to exactly how the budget is spent on R2, or MTTR.

19. MTTR (hours) % of Total Budget Spent on MTTR Reduction Experimental MTTR curve – convex (test two)

20. Reference Path Unavailability % of Total Budget Spent on MTTR Reduction(Balance goes to R2 Enhancement) Test two result

21. Test two discussion • This is the curve portraying whereit is very difficult (costly) to obtain any MTTR reductions. • We think less plausible a shape,but worthwhile as a “what if” to show the range of strategythis analysis can inform an operator on. • In this case, the preferred strategy is strongly on capacity addition to enhance R2,

22. Concluding comments • Suffices to show that at least conceptually an optimum combined strategy in MTTR and R2 investment exists. • A unique / interesting phenomenon arising specifically in the context of networks that are already “R1=1” survivable by design. (Note MTTR has no special role for R1=1 design) • Once a network is R1=1, however, MTTR takes on new importance because thereafter U ~ O(MTTR-2) • Other factors to consider: • MTTR improvements are probably annual expenses, manpower • R2 improvement is, however, probably a capital investment. • Added capacity never hurts in a network (throughput, flexibility, grown) • But fast repairs will be directly appreciated by users too

23. thank you Thank You (And thanks again to the great question from the DRCN 2005 Panel Discussion !) www.trlabs.ca www.ualberta.ca www.telus.com