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A Framework for Network Survivability Characterization

A Framework for Network Survivability Characterization. Soung C. Liew and Kevin W. Lu IEEE Journal on Selected Areas in Communications, January 1994 (ICC, 1992). Wendy Wen OPlab, IM, NTU. OUTLINE. Introduction Survivability of a Centralized Ring Network under Link Failures

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A Framework for Network Survivability Characterization

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  1. A Framework for Network Survivability Characterization Soung C. Liew and Kevin W. Lu IEEE Journal on Selected Areas in Communications, January 1994 (ICC, 1992) Wendy Wen OPlab, IM, NTU

  2. OUTLINE • Introduction • Survivability of a Centralized Ring Network under Link Failures • General Procedure for Finding Survivability Function • Finding Survivability Function for a Network • Conclusions

  3. OUTLINE • Introduction • Survivability of a Centralized Ring Network under Link Failures • General Procedure for Finding Survivability Function • Finding Survivability Function for a Network • Conclusions

  4. Objective • This paper attempts to formulate a general framework that both includes and extends the existing definitions for network survivability.

  5. Survivability Function • The probability that a fraction s of the nodes are connected to the central node. • S : network survivability, which is a random variable • e: sample point • E : sample space, E = {e} • Pe: probability of each e • Se: probability of nodes connected to the central node

  6. Advantage • A number of different quantities of interest can be derived from the function. • E[S] , s* , sr , p0

  7. OUTLINE • Introduction • Survivability of a Centralized Ring Network under Link Failures • General Procedure for Finding Survivability Function • Finding Survivability Function for a Network • Conclusions

  8. Assumption • S = fraction of nodes connected to the central node under • All links are bidirectional. • The number of Node is very large. • link failures = n • A link failure is equally likely to be located anywhere. • The locations of the n failures are independent. • n≧2 self-healing s = Con.

  9. Objective • Derive the corresponding survivability function:

  10. Derivation(1) • Dividing into many small segments, each of length △s. • Size of the sample space is

  11. Derivation(2) • Each of these sample points is equally likely, Ns: the number of ways to make n cuts that result in a survivability of s.

  12. Derivation(3):Find Ns • n(n-1)ways of choosing two cuts to be Cland Cr • s/△sways of putting the two adjacent cuts, fromClto Cr • Ways of the remaining (n-2) cuts is .

  13. Derivation(4) • By definition, • Remind that,

  14. Derivation (6): Find ps(S) • Let Ncbe the r.v. associated with the number of cuts. • where δ(x) is the impulse function 總和定理 Pr of n=0 and n=1 Pr of n≧2 P[S=s | n] , from eq.12 1, x=0 0, otherwise δ(x) =

  15. Derivation (7): Find ps(S) • Let MGF of Ncis • Then, • Assume Poisson distribution, • Thus, Fr.eq. 17: pdf of Poisson MGF of Poisson P(N=0) P(N≧2)=mgf(2)(1-s) P(N=1)

  16. OUTLINE • Introduction • Survivability of a Centralized Ring Network under Link Failures • General Procedure for Finding Survivability Function • Finding Survivability Function for a Network • Conclusions

  17. Procedure • Specify disaster type • Define “goodness” of networks • List the sample points {e}, or all combinations of events • Determine the survivability Se • Determine or assign probability of each event e • Calculate survivability function

  18. Step 1. Specify disaster type • Different disaster types may have different effects on networks. • severe thunderstorm • cable cut

  19. Step 2. Define “goodness” of networks • We may obtain results depending on the features of the network for which we are calculating survivability. • the number of subscribers connected to a central node • the revenue collected by the network operator

  20. Step 3. List all combinations ofevents • Sample space may simply be too large. • It maybe can only be done effectively by a computer.

  21. Step 4. Determine Se • This calculation will depend on our definition of survivability. • If as example above, then we would need an efficient algorithm.

  22. Step 5. Determine Pe • This should be based on past observations or experience. • If the disaster happens so rarely, one will need to use one’s judgement when assigning probabilities.

  23. Step 6. Calculate survivability function • By summing the probabilities of all sample points with the same survivability.

  24. OUTLINE • Introduction • Survivability of a Centralized Ring Network under Link Failures • General Procedure for Finding Survivability Function • Finding Survivability Function for a Network • Conclusions

  25. Assumption • 24 nodes • 26 links • the number associated with each link is its length • 69 DS3 fiber-optic transmission systems between 29 node pairs

  26. 3 2 4 Table I. DS3 demands between nodes of n network.

  27. Step 1. Specify disaster type • Hurricanes

  28. Step 2. Define “goodness” of networks • Total number of surviving DS3’s under link failures

  29. Step 3. List all combinations ofevents • Localized disasters: the network survivability can be easily found. • Hurricane: 226 = 67,108,864 possible combinations of link failures. • Assume that more than four link failures are highly unlikely.

  30. Step 4. Determine Se • For each event e,the survivability is Se = (surviving DS3’s) / 69

  31. Step 5. Determine Pe(1) • Assume that, • link failures are independent • probability of a link failure is proportional to its length ε: to reflect the extent of damage expected of the hurricane,

  32. Step 5. Determine Pe(2) • Probabilities of single, double,triple, and quadruple link failures are: Pr of a link failure Pr of the others Pr of two link failures Pr of the others Pr of three link failures Pr of the others Pr of four link failures Pr of the others

  33. Step 6. Calculate survivability function (1) • For illustration, we condense all survivability within the intervals, (0.02i -0.1 , 0.02i +0.1] i=1, 2 ,..., 50 • Show survivability functions for ρ= 0.1 and ρ= 0.2. • Remind that,

  34. ρ= 0.1 E [ S ]≈0.923 S*≈ 0.28 S10≈ 0.8 Po≈ 0 ρ= 0.2 E [ S ]≈0.822 S*≈ 0.28 S10≈ 0.72 Po≈ 0

  35. Step 6. Calculate survivability function (2) • When increasing ρfrom 0.1 to 0.2, • P(s=1) : decreases from 0.341 to 0.11 • E[S] : decreases from 0.923 to 0.822 • S10 : decreases from 0.8 to 0.72 • S* : unchanged

  36. Step 6. Calculate survivability function (3) • Although the worst-case survivability is 0.28, it corresponds to two events of quadruple link failures • links 3-6, 5-6, 6-7 and 6-8 • links 3-6, 5-6, 6-7 and 8-15

  37. links 3-6, 5-6, 6-7, 6-8 9 9 links 3-6, 5-6, 6-7, 8-15 7 7 25 25 10 8

  38. OUTLINE • Introduction • Survivability of a Centralized Ring Network under Link Failures • General Procedure for Finding Survivability Function • Finding Survivability Function for a Network • Conclusions

  39. Conclusions • Network survivability is characterized by a survivability function. • Various quantities of interest can be derived from the survivability function. • This framework provides a unified and practical approach to analyzing and designing highly survivable communications networks.

  40. The End Thank you for your listening~

  41. Fig. 1. A ring network with node failures due to a thunderstorm

  42. 3 3+2 2 3+2+4 4 Table II. DS3’s lost due to link failures of a network.

  43. min li max li Fig. 6. A network for survivability characterization.

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