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Scalable Reliable Multicast in Wide Area Networks Sneha Kumar Kasera Department of Computer Science University of Massachusetts, Amherst.

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Presentation on theme: "Scalable Reliable Multicast in Wide Area Networks Sneha Kumar Kasera Department of Computer Science University of Massachusetts, Amherst."— Presentation transcript:

1 Scalable Reliable Multicast in Wide Area Networks Sneha Kumar Kasera Department of Computer Science University of Massachusetts, Amherst

2 Why Multicast ? multiple unicast broadcastmulticast one sender three receivers

3 Why Reliable Multicast ? applications one-to-many file transfer information updates (e.g., stock quote, web cache updates) shared whiteboard multicast lossy network

4 Goal design, evaluate multicast loss recovery approaches that make efficient use of end-host, network resources scale to several thousand receivers spanning wide area networks

5 Feedback Implosion NAK implosion ? NAK suppression (using timers) NAK aggregation (by building hierarchy) pktACK sender receiver receivers pkt ACK pkt NAK loss problem: ACK implosionsolution: use NAKs

6 sender loss original transmission loss pkt lost retransmission unicast multicast

7 Problem of Retransmission Scoping if same channel for retransmissions, retransmissions go everywhere how to shield receiver from loss recovery due to other receivers ? sender loss original transmission loss retransmission

8 Loss Recovery Burden when #receivers large, each pkt lost at some rcvr with high probability sender retransmits almost all pkts several times how to share burden of loss recovery ? sender loss pkt 1 pkt 4 pkt 2 pkt 3 loss retransmits pkts 1, 2, 3, 4

9 scoping retransmissions using multiple multicast channels server-based local recovery performance benefits resource requirements “active” repair services signaling for locating, invoking, revoking services router support Thesis Contributions

10 scoping retransmissions using multiple multicast channels server-based local recovery performance benefits resource requirements “active” repair services signaling for locating, invoking, revoking services router support summary and future directions Overview

11 one channel for original transmissions, A orig additional channels for retransmissions, pkt k sent on A k on detecting loss of pkt k, receiver joins A k recovers packet k leaves A k Scalable Reliable Multicast Using Multiple Multicast Channels sender loss A orig loss AkAk Kasera, Kurose, Towsley, ACM SIGMETRICS Conference ‘97

12 Issues how much is performance improved ? receiver, sender processing network bandwidth if (multicast channel IP multicast group), realistically only finite channels available ! overhead of join, leave operations ? router support for multiple multicast channels ?

13 Analysis rcvrs unicast NAKs to sender infinite channels available system model one sender, R receivers independent loss, probability p NAKs not lost E[Y] = E[Y p ] + pE[Y j ] + pE[Y n ]/(1-p) + p 2 E[Y t ]/(1-p) determined various proc times by instrumenting Linux kernel Y = total per pkt rcv proc time Y p = rcvd pkt proc time Y j = join, leave proc time Y n = NAK proc time Y t = timer proc time NAK processingtimer processing join, leave processing rcvd pkt processing

14 considerable reduction in rcvr processing costs by using infinite channels example: when R = 1000, p = 0.05, processing cost reduces by approx. 65% similar behavior observed for protocols that multicast NAKs for NAK suppression Receiver Processing Cost Reduction

15 recycle G retransmission channels, retransmit pkt k on A k mod G example, G = 3 Finite # of Retransmission Channels transmit retransmit pkt 1 on (1) 1234 5 retransmit pkt 4 on (1) lost at r1lost at r2 lost at r1 lost at r2 received at r1 received at r2 received at r1 11111 44

16 find #unwanted pkts, U, at receiver due to using G channels only model same as before transmit with interval  retransmit with interval  ’ (if pending NAK) U depends upon G, p, R,  /  ’ receiver processing cost, E[Y’] = E[Y] + E[U]E[Y p ] Finite # of Retransmission Channels unwanted pkt processing

17 How many channels do we need ? find minimum #channels s.t. increase in cost within 1% small #channels for wide range of p,  /  ’, R #channels = 0.5 sensitive to low  /  ’ /’/’

18 Summary (part 1) use of multiple multicast channels reduces receiver processing small to moderate #channels achieve almost perfect retransmission scoping implementation using router support also saves network bandwidth sender still bottleneck, no improvement in protocol performance

19 Local Recovery server and/or other receivers aid in loss recovery distribution of loss recovery burden possible reduction in network bandwidth recovery latency retransmission scoping sender loss transmission loss local domains server

20 scoping retransmissions using multiple multicast channels server-based local recovery performance benefits resource requirements “active” repair services signaling for locating, invoking, revoking services router support summary and future directions Overview

21 repair servers co-located with routers at strategic locations placement of application level repair service in routers repair servers cache recent pkts receivers, repair servers, recover lost pkts from upper level repair servers, sender repair server Repair Server Based Local Recovery sender receivers Kasera, Kurose, Towsley, IEEE INFOCOM ‘98

22 Issues how much is performance improved over traditional local recovery approaches ? SRM: dynamically elect receiver for every loss RMTP, LBRM: designated receiver, logger for supplying repairs where to place repair servers ? what are repair server resource requirements ?

23 based on [YKT ‘97] loss free backbone, sites loss at source link, tails temporally independent loss, probability p sender receivers backbone tail site local domain source link System Model

24 based on [YKT ‘97] loss free backbone, sites loss at source link, tails temporally independent loss, probability p sender receivers backbone tail site local domain source link System Model designated receiver

25 based on [YKT ‘97] loss free backbone, sites loss at source link, tails temporally independent loss, probability p sender receivers backbone tail site local domain source link System Model repair server

26 metrics throughput = 1/max(sender-processing time, receiver- processing time) bandwidth usage = total bytes transmitted over all links per correct transmission analysis: similar approach as in previous problem (optimistic bounds for SRM) Performance Evaluation

27 repair server-based (RSB) compared to SRM: throughput upto 2.5 times, bandwidth reduction 60% DR-based (DRB): throughput upto 4 times, bandwidth reduction 35% Performance Comparison

28 additional sender retransmission required if some domains without repair servers place repair servers in high loss domains first homogeneous loss: high % domains require repair server Insufficient Repair Servers 20% tail loss in 20% domains, 1% tail loss in 80% domains

29 theoretically: infinite realistically: allot finite buffers replace pkts when buffers full if required, replaced pkts recovered upstream size depends upon amount of upstream recovery pkt arrival process, buffer holding time replacement policy Repair Server Buffer Requirements (per session) example: when p = 0.05, 15 buffers ensure almost perfect local recovery

30 examine three policies FIFO, LRU FIFO-MH: FIFO with minimum buffer holding time = one retransmission interval FIFO-MH shows little improvement over FIFO LRU performs better than FIFO only when #buffers large Buffer Replacement Policies example: arrival rate = 128pkts/sec retransmission interval from round trip time traces

31 repair server-based approach exhibits superior performance over traditional approaches repair server placement - above loss, higher loss domains first buffer requirement several 10s of buffers (per session) simple FIFO replacement policy sufficient how to make repair server approach dynamic ? Summary (part 2)

32 scoping retransmissions using multiple multicast channels server-based local recovery performance benefits resource requirements “active” repair services signaling for locating, invoking, revoking services router support summary and future directions Overview

33 Active Repair Service repair server functionality as active repair service design repair service-based protocol, AER locate, invoke repair services using source path messages (SPMs) minimal router support required for interception of SPM, subcast S SPMRS1 SPMRS2 SPMS SPMs multicast but intercepted NAKs take reverse path

34 scoping retransmissions using multiple multicast channels server-based local recovery performance benefits resource requirements “active” repair services signaling for locating, invoking, revoking services router support Thesis Contributions

35 model cost of additional network resources buffer requirements multiple sessions other applications (e.g., web caching) composable multicast services other multicast research revisit IP multicast service model congestion control pricing Future Directions

36 identify performance enhancing services, examples feedback aggregation selective forwarding repair, rate conversion, log services invoke/revoke services based on application requirements network conditions Composable Multicast Services (Work in Progress) sender protocol feedback aggregation rcvr protocol rcvr protocol rcvr protocol rcvr protocol issues: implementing composability signaling mechanism (SPM++) measurement-based infrastructure rate conversion


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