12/09/01 1 SCAMP: lightweight membership service for gossip- based protocols Ayalvadi Ganesh, Anne-Marie Kermarrec & Laurent Massoulié Microsoft Research.

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Presentation transcript:

12/09/01 1 SCAMP: lightweight membership service for gossip- based protocols Ayalvadi Ganesh, Anne-Marie Kermarrec & Laurent Massoulié Microsoft Research Cambridge, UK

12/09/012 Probabilistic multicast Scalable and reliable group communication Gossip-based algorithms Scalable Reliable Probabilistic guarantees Graceful degradation in the presence of failure Non scalable membership protocol

12/09/013 Background: gossip-based protocol Fanout = k Probability of reliable delivery : P = exp(-exp(-s)) If k = log n + s

12/09/014 Background: gossip-based protocol

12/09/015 Membership Global knowledge Storage and consistency maintenance Partial knowledge requires coordination Fanout setting to achieve a given probability of reliable delivery Fanout update

12/09/016 Scamp: Self-organizing membership protocol Partial knowledge of the membership: local view Fanout automatically set = size of the local view Fanout evolves naturally with the size of the group Size of local views converges towards clog(n)

12/09/017 Scamp: Subscription (c=1) View sizes automatically converge to log(n) Gossip protocol: Each node gossips to all the members of its view

12/09/018 Subscription algorithm Ser s s s P=1/sizeof view (1-P) P=1/sizeof view (1-P) Subscription forwarded S Subscription to a random member s s s s s s View sizes automatically converge to log(n) Each node gossips to all the members of its view

12/09/019 Subscription algorithm Local view

12/09/0110 Lease on subscriptions Lease associated with each subscription Periodically nodes have to re-subscribe Nodes having failed permanently will time out Re-balance the partial views

12/09/0111 Unsubscriptions Unsubscription broadcast with local view When a node removes the unsubscribed node, it picks up randomly another node to incorporate in its view

12/09/0112 Unsubscriptions Unsub (0), [1,4,5] Local view z x y x y z

12/09/0113 Theoretical Analysis System modelled as random directed graph D(N) = Average out-degree for N-nodes system Subscription adds D(N)+1 directed arcs, so (N+1) D(N+1) = N D(N) + D(N)+1 Solution of this recursion is D(N)=D(1)+1/2+1/3+…+1/N Log(N)

12/09/0114 Scamp:Experiments Simulation results Convergence of view size Confirm theoretical analysis Impact of lease Reliability Comparison with traditional gossip-based Attest to the good quality (uniformity) of views

12/09/0115 Distribution of view size Log=12.2 Log=13.12

12/09/0116 Impact of lease 5000 nodes View size Number of nodes mean=7.53 mean=8.47

12/09/0117 Reliability: 5000 node system Number of failures Reliability SCAMP Global membership knowledge, fanout=8 Global membership knowledge, fanout=9

12/09/0118 Conclusion Membership protocol Scalable: local view Self-organizing: truly peer-to-peer Local views naturally converge towards the right value without global directive Theoretical analysis and simulations On going work Integration of locality

12/09/0119 Centralized subscriptions