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Randomized Rumour Spreading on Random k -trees Abbas Mehrabian - PowerPoint PPT Presentation

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Randomized Rumour Spreading on Random k -trees Abbas Mehrabian amehrabi@uwaterloo.ca University of Waterloo 5 May 2014 Monash University Abbas (Waterloo) Rumour spreading 5 May 1 / 58 Protocol definition Demers, Gealy, Greene, Hauser,

  1. Randomized Rumour Spreading on Random k -trees Abbas Mehrabian amehrabi@uwaterloo.ca University of Waterloo 5 May 2014 Monash University Abbas (Waterloo) Rumour spreading 5 May 1 / 58

  9. Protocol definition Demers, Gealy, Greene, Hauser, Irish, Larson, Manning, Shenker, Sturgis, Swinehart, Terry, Woods’87 1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-step 1 , 2 , . . . , every informed vertex tells the rumour to a random neighbour. Abbas (Waterloo) Rumour spreading 5 May 9 / 58

  10. Protocol definition Demers, Gealy, Greene, Hauser, Irish, Larson, Manning, Shenker, Sturgis, Swinehart, Terry, Woods’87 1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-step 1 , 2 , . . . , every informed vertex tells the rumour to a random neighbour. Remark 1. Informed vertex may call a neighbour in consecutive steps. Remark 2. If a vertex receives the rumour at time t , it starts passing it from time t + 1. Abbas (Waterloo) Rumour spreading 5 May 9 / 58

  11. Protocol definition Demers, Gealy, Greene, Hauser, Irish, Larson, Manning, Shenker, Sturgis, Swinehart, Terry, Woods’87 1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-step 1 , 2 , . . . , every informed vertex tells the rumour to a random neighbour. Remark 1. Informed vertex may call a neighbour in consecutive steps. Remark 2. If a vertex receives the rumour at time t , it starts passing it from time t + 1. inform-time( v ): the first time v learns the rumour. Spread Time: the first time everyone knows the rumour. Abbas (Waterloo) Rumour spreading 5 May 9 / 58

  12. Application: distributed computing Abbas (Waterloo) Rumour spreading 5 May 10 / 58

  13. Application: distributed computing Rumour spreading advantages: � Simplicity, locality, no memory � Scalability, reasonable link loads � Robustness Abbas (Waterloo) Rumour spreading 5 May 10 / 58

  14. Example: a path Abbas (Waterloo) Rumour spreading 5 May 11 / 58

  15. Example: a path inform − time ( 0 ) = 0 Abbas (Waterloo) Rumour spreading 5 May 11 / 58

  16. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 Abbas (Waterloo) Rumour spreading 5 May 12 / 58

  17. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 1 / 2 ) Abbas (Waterloo) Rumour spreading 5 May 13 / 58

  18. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 1 / 2 ) inform − time ( 3 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) Abbas (Waterloo) Rumour spreading 5 May 14 / 58

  19. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 1 / 2 ) inform − time ( 3 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) inform − time ( 4 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) Abbas (Waterloo) Rumour spreading 5 May 15 / 58

  20. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 1 / 2 ) inform − time ( 3 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) inform − time ( 4 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) E [ Spread Time ] = 1 + 3 × 2 = 7 Abbas (Waterloo) Rumour spreading 5 May 16 / 58

  21. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 1 / 2 ) inform − time ( 3 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) inform − time ( 4 ) = 1 + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) + Geo ( 1 / 2 ) E [ Spread Time ] = 1 + 3 × 2 = 7 = 2 n − 3 Abbas (Waterloo) Rumour spreading 5 May 17 / 58

  22. Example: a star Abbas (Waterloo) Rumour spreading 5 May 18 / 58

  23. Example: a star When k + 1 vertices are informed and n − 1 − k uninformed, n − 1 after n − 1 − k more rounds a new vertex will be informed. Abbas (Waterloo) Rumour spreading 5 May 18 / 58

  24. Example: a star When k + 1 vertices are informed and n − 1 − k uninformed, n − 1 after n − 1 − k more rounds a new vertex will be informed. E [ Spread Time ] = n − 1 n − 1 + n − 1 n − 2 + · · · + n − 1 + n − 1 ≈ n ln n 2 1 Abbas (Waterloo) Rumour spreading 5 May 18 / 58

  25. Example: a complete graph Abbas (Waterloo) Rumour spreading 5 May 19 / 58

  26. Example: a complete graph [ Pittel ′ 87 ] E [ Spread Time ] ≈ log 2 n + ln n Abbas (Waterloo) Rumour spreading 5 May 19 / 58

  27. Other known results With probability approaching 1, for any starting vertex, 1. max { diameter ( G ) , log 2 n } ≤ Spread Time ≤ ( 1 + o ( 1 )) n ln n [Elsässer and Sauerwald’06] Abbas (Waterloo) Rumour spreading 5 May 20 / 58

  28. Other known results With probability approaching 1, for any starting vertex, 1. max { diameter ( G ) , log 2 n } ≤ Spread Time ≤ ( 1 + o ( 1 )) n ln n [Elsässer and Sauerwald’06] 2. Spread Time of H d = Θ ( d ) [Feige, Peleg, Raghavan, Upfal’90] H 3 Abbas (Waterloo) Rumour spreading 5 May 20 / 58

  29. Other known results With probability approaching 1, for any starting vertex, 1. max { diameter ( G ) , log 2 n } ≤ Spread Time ≤ ( 1 + o ( 1 )) n ln n [Elsässer and Sauerwald’06] 2. Spread Time of H d = Θ ( d ) [Feige, Peleg, Raghavan, Upfal’90] H 3 3. If pn ≥ ( 1 + ε ) ln n then Spread Time of G ( n , p ) = Θ ( log n ) [Feige et al.’90] Abbas (Waterloo) Rumour spreading 5 May 20 / 58

  30. Improving the protocol Uninformed vertices ask the informed ones... Abbas (Waterloo) Rumour spreading 5 May 21 / 58

  31. The push-pull protocol Demers, Gealy, Greene, Hauser, Irish, Larson, Manning, Shenker, Sturgis, Swinehart, Terry, Woods’87 1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-step 1 , 2 , . . . , every informed vertex sends the rumour to a random neighbour (PUSH); and every uninformed vertex queries a random neighbour about the rumour (PULL). Abbas (Waterloo) Rumour spreading 5 May 22 / 58

  32. The push-pull protocol Demers, Gealy, Greene, Hauser, Irish, Larson, Manning, Shenker, Sturgis, Swinehart, Terry, Woods’87 1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-step 1 , 2 , . . . , every informed vertex sends the rumour to a random neighbour (PUSH); and every uninformed vertex queries a random neighbour about the rumour (PULL). Remark 1. Vertices may call the same neighbour in consecutive steps. Remark 2. If a vertex receives the rumour at time t , it starts passing it from time t + 1. Spread Time: the first time everyone knows the rumour. Abbas (Waterloo) Rumour spreading 5 May 22 / 58

  33. Example: a star push protocol: n ln n rounds push-pull protocol: 1 or 2 rounds Abbas (Waterloo) Rumour spreading 5 May 23 / 58

  34. Example: a path Abbas (Waterloo) Rumour spreading 5 May 24 / 58

  35. Example: a path inform − time ( 0 ) = 0 Abbas (Waterloo) Rumour spreading 5 May 24 / 58

  36. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 Abbas (Waterloo) Rumour spreading 5 May 25 / 58

  37. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + min { Geo ( 1 / 2 ) , Geo ( 1 / 2 ) } = 1 + Geo ( 3 / 4 ) Abbas (Waterloo) Rumour spreading 5 May 26 / 58

  38. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 3 / 4 ) inform − time ( 3 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) Abbas (Waterloo) Rumour spreading 5 May 27 / 58

  39. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 3 / 4 ) inform − time ( 3 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) inform − time ( 4 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) + 1 Abbas (Waterloo) Rumour spreading 5 May 28 / 58

  40. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 3 / 4 ) inform − time ( 3 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) inform − time ( 4 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) + 1 E [ Spread Time ] = 2 + 2 × 4 / 3 = 14 / 3 Abbas (Waterloo) Rumour spreading 5 May 29 / 58

  41. Example: a path inform − time ( 0 ) = 0 inform − time ( 1 ) = 1 inform − time ( 2 ) = 1 + Geo ( 3 / 4 ) inform − time ( 3 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) inform − time ( 4 ) = 1 + Geo ( 3 / 4 ) + Geo ( 3 / 4 ) + 1 E [ Spread Time ] = 2 + 2 × 4 / 3 = 14 / 3 = 4 3 n − 2 ( versus 2 n − 3 for push ) Abbas (Waterloo) Rumour spreading 5 May 30 / 58

  42. Example: a complete graph push: log 2 n + ln n + o ( log n ) [Pittel’87] push-pull: ≤ log 3 n + o ( log n ) [Karp, Schindelhauer, Shenker, Vöcking’00] Abbas (Waterloo) Rumour spreading 5 May 31 / 58

  43. Other results on push-pull protocol 1. Barabasi-Albert preferential attachment graph has Spread Time Θ ( log n ) , PUSH alone has Spread Time poly ( n ) . 2. Random graphs with power-law expected degrees (a.k.a. the Chung-Lu model) with exponent ∈ ( 2 , 3 ) has Spread Time Θ ( log n ) . 3. If Φ is Cheeger constant (conductance) and α is the vertex expansion (vertex isoperimetric number), Spread Time ≤ C max { Φ − 1 log n , α − 1 log 2 n } . Abbas (Waterloo) Rumour spreading 5 May 32 / 58

  44. Let’s see some simulation results... Abbas (Waterloo) Rumour spreading 5 May 33 / 58

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