1. Reliable Multicast Revisited Reliable Multicast –One-to-many and many-to-many communication –Dynamic group membership –Reliability in the transmission of packets –Trade-off between recovery latency and overhead Research Objective –Design novel reliable multicast protocol –Formally analyze protocol’s performance

2. Scalable Reliable Multicast [Floyd, et. al.] Application layer – uses IP multicast as primitive Based on NACKs and retransmissions All members share in loss recovery overhead Limits duplicate packet requests/replies using: –Deterministic suppression Scheme for allowing ancestors to suppress descendants Schedule requests/replies proportionately to distance to source –Probabilistic suppression Scheme for allowing siblings to suppress each other Spread out scheduling of requests/replies

3. Our Reliable Multicast Protocol Objective: Exploit locality in packet losses [Bolot, et. al., Yajnik, et. al., Handley] Protocol: Inspired by SRM (w/ archiving) –Adopt deterministic suppression –Use caching scheme to suppress siblings Cache optimal requestor/replier pair Optimistically predict the location of future losses Build a hierarchy of requestor/replier pairs

4. Illustration the Caching Scheme Leader selected based on: Distance to source Order of identifiers

5. Protocol Performance Rationale Save latency incurred by probabilistic suppression Following the election of requestor/replier pairs –Minimize recovery latency by utilizing optimal requestor/replier pairs –Obtain single requests/replies Cost of building and maintaining leader hierarchy –Duplicate messages during first round losses –Duplicate messages upon cache misses

6. Protocol Performance Analysis Performance metrics –Loss recovery latency: Time b/w detection of packet loss and reception of first retransmission –Loss recovery overhead: # of messages multicast pertaining to the recovery of a particular loss Assumptions: –No recovery packet losses –Inter-host delay estimates accurate in the sense of receiver ordering

7. Performance Analysis Approach I. Absolute Performance Analysis –State recovery latency claims for cache hits/misses –Measure cache hit/miss rates –State overall performance claims II. Comparative Performance Analysis –State performance claims wrt SRM

8. I. Absolute Performance Analysis Recovery Latency: t recovery < c t SA * + t AB + d t AB * + t BA where S = source, A = requestor, B = replier c,d : delay parameters of deterministic suppression t SA *, t AB * : inter-host delay estimates t AB,, t BA : actual inter-host delays Optimal requestor/replier pair given by: –Choosing requestor closer to loss location (source) –Choosing replier closer to loss location (requestor)

9. Optimal Requestor/Replier Pair S A B (A,B) – optimal requestor/replier pair

10. Cache Hit Performance All requestors, e.g., C,D, incur latency of optimal requestor/replier pair (A,B): t recovery ~ c t SA * + t AB + d t AB * + t BA S A B CD

11. Cache Miss Performance Types of miss depends on loss location –Higher:Leader competes for sending request –Lower:Non-leaders must time-out waiting for the request of their leader If deterministic suppression delay > delay in receiving leader request then no extra delay else additional delay incurred What is the cost of this additional delay? How often is it incurred? How does the worst case cache miss compare to SRM?

12. Cache Hit/Miss Rate Cache hit rate measurements for available multicast traces by Yajnik, et. al.

13. II. Comparative Performance Analysis Compare the recovery latency and overhead to those of SRM –Probabilistic suppression latency saved –Cache hits result in single request/reply –Cache hits ensure optimal delay for all receivers sharing hit –Cache misses? How do they affect performance?

14. Future Work Complete our performance analysis work –Analyze the performance of the leader-hierarchy –Evaluate/measure the effect of the cache hit/miss rate Do cache hit savings outweigh miss delays? –Analyze performance in terms of message overhead –How do losses pertaining to recovery affect performance Condition analysis on the # of losses

15. Future Protocol Directions Optimistic/Expedited recovery –Leader requestor immediately unicasts request to leader replier Local error recovery – Subcasting? Application of caching to router-assisted protocols