FEC and Pseudo-ARQ for Receiver-driven Layered Multicast Philip A. Chou, Alex Mohr, Albert Wang, Sanjeev Mehrotra (Microsoft, University of Washington, Stanford)

Problem Efficient and robust broadcast of real-time audio and video over the near-term Internet –Best-effort packet loss, jitter, out-of-sequence –Heterogeneous transmission rate, loss rate, delay, jitter, receivers –Feedback available

Problem Find ways to multicast real-time audio and video efficiently and robustly over the near-term Internet –Best-effort packet loss, jitter, out-of-sequence –Heterogeneous transmission rate, loss rate, delay, jitter, receiver capacity –Dynamic Influence design of network services in longer term

Outline Multicast Receiver-driven Layered Multicast FEC and Pseudo-ARQ

Multicast Mechanism for broadcasting in packet networks: any receiver able to receive broadcast packets by tuning in to broadcast address Our focus: IP networks Protocols: –How to dynamically maintain a multicast routing tree IGMP, DVMRP/PIM/CBT/… –How to forward packets along the tree IP Multicast

Packet Forwarding in a Multicast Routing Tree S RR RRR 12 S,G | data : S,G - 1,2 : multicast routing table packetS = Source Address G = Multicast Group Address

Grafting / Joining / Subscribing S RR RRRRR 12 Join S,G : S,G - 1,2 : multicast routing table Join S,G : S,G - 1 : multicast routing table 1

Pruning / Leaving / Unsubscribing S RR RRR R multicast routing table R Leave S,G : S,G - 1 : 1 Leave S,G : S,G- 1, 2 : multicast routing table 1

Observations Bandwidth is conserved. Sender has no knowledge of receivers (likewise any interior router). Scalable: As new receivers join, no new resources (bandwidth, computation) are needed at the sender, and resources needed at any individual router are bounded. Joining and Leaving are a form of feedback.

Growth of Multicast Infrastructure MBONE has grown from 901 routers in 1994 to routers in 1998 Commercial routers (e.g., Cisco) have been multicast enabled for last two years ISPs (e.g., have begun to provide multicast service Intranets are widely multicast enabled Much research and standardization work

Reliable Multicast –1-to-M file transfer, distributed software updates, synch. of distributed databases, filesystems –must be reliable, but delay is not constrained Real-time Multicast –for broadcast of live or pre-recorded audio/video –need not be reliable, but delay is constrained Types of Multicast Applications

Reliable Multicast ARQ-based error control –need to avoid repeat request implosion –protocols use hierarchical re-transmitters (SRM, RMTP, RAMP, RMP, …) FEC-based error control –digital fountain Multiple channels for flow control

Real-time Multicast Error resilient source coding for error control –in MBONE tools (nv), commercial systems FEC-based error control –in MBONE tools (RAT), commercial systems –fixed amount of redundancy ARQ-based error control –commercial systems, LVMR Layered source coding for flow control

Receiver-driven Layered Multicast (S. McCanne 96) Base layer... to multicast group G0 Enh. layer 1... to multicast group G1 Enh. layer 2... to multicast group G2 time Code source in layers (base, enh1, enh2, …) Send each layer to different multicast group Receivers subscribe to as many layers as desired S0 t S0 t+1 S0 t+2 S0 t+3 S0 t+4 S0 t+5 S1 t S1 t+1 S1 t+2 S1 t+3 S1 t+4 S1 t+5 S2 t S2 t+1 S2 t+2 S2 t+3 S2 t+4 S2 t+5

Dynamic Joining/Leaving S RR RR R Receivers subscribe and unsubscribe according to instantaneous capacity transmission rate loss prob 1 0

The Case for FEC S RR RR R Problem is that ambient congestion may always be present transmission rate loss prob 1 0

FEC for Receiver-driven Layered Multicast Amount of redundancy must be receiver- driven to deal with heterogeneity, dynamics Generate FEC in layers, using a systematic rate-compatible code (for each source layer) Send each layer to different multicast group At each receiver, subscribe to number of source layers, number of parity layers for each source layer, to optimize received quality

Generation of Parity Packets Block each source layer into K packets per block Apply systematic Reed-Solomon type code to packets (bytewise) to produce N-K parity packets Source layer... to multicast group Gx Parity layer 1... to multicast group Gx.1 Parity layer 2... to multicast group Gx.2 Parity layer 3... to multicast group Gx.3 S tK S tK+1 S tK+2 S (t+1)K P t+1,1 P t,1 P t+1,2 P t,2 P t+1,3 P t,3 S (t+1)K+1 S (t+1)K+2 K N-K

Optimization at Each Receiver Measure transmission rate and loss probability For this transmission rate and loss probability, minimize expected distortion (over number of source layers, and number of parity layers for each source layer) Subscribe to optimal number of source layers, and optimal number of parity layers for each source layer

Expected Distortion and Rate layer D0D0 D1D1 … D8D8 D2D D3D3 … R i =N i /K p i =p(R i ) raw loss prob

Lagrangian Optimization 0132 R=N /K S1S1 S2S2 S3S3 …

Unequal Error Protection

The Case for ARQ FEC does not achieve capacity C = 1 p ARQ makes optimal use of forward channel Adapts to loss (erasure) probability p Used extensively for data transmission (e.g., TCP) and media transmission (e.g., VOD) Must avoid repeat-request implosion Observe: for broadcast of real-time media, delay (number of repeat-requests) is bounded

Pseudo-ARQ for Receiver-driven Layered Multicast Sender transmits delayed versions of source Receivers request repeats by subscribing and unsubscribing to delayed versions Source stream... to multicast group G Delayed stream 1... to multicast group G1 Delayed stream 2... to multicast group G2 time StSt S t+1 S t+2 S t+3 S t+4 S t+5 StSt S t-1 S t-2 StSt S t+1 S t+2 S t+3 S t+4 S t+2

S tK S tK+1 S tK+2 S (t+1)K P t+1,1 P t,1 P t,2 P t-1,2 P t,3 P t-1,3 S (t+1)K+1 S (t+1)K+2 Hybrid FEC & Pseudo-ARQ Sender delays parity packets Repeated info is actually parity info Source layer... to multicast group Gx Parity layer 1... to multicast group Gx.1 Parity layer 2 (delayed 1 block)... to multicast group Gx.2 Parity layer 3 (delayed 1 block)... to multicast group Gx.3 K=3 W=2 waves (decision epochs) Delay is blocklength times number of waves

Reduction in Network Traffic

Markov Decision Process Finite-state stochastic process in which a decision can be made at each step to influence the transition probabilities, in order to maximize an expected reward Sequence of decision rules is a policy Optimal policy, which minimizes expected cost (D+ R) of paths through state space, can be found by dynamic programming

State Space for FEC/Pseudo-ARQ # pkts to req # pkts recvd # pkts to req # pkts recvd

Caveats No experiments so far, only analysis –no actual network transmissions, no source coding, no channel coding –source is modeled as D= 2 2 2R –channel is modeled as iid 20% packet loss, no packet jitter or resequencing –assumed no join or leave latencies Little analysis of aggregate behavior

Analyzed Systems 1- No error protection (original RLM) 2- Equal error protection, redundancy determined by sender; K=8; N=11,14,17,20 3- Unequal error protection, determined by receiver; K=8; N i =N i * (RLM w/FEC) 4- FEC and Pseudo-ARQ; W=1,2,4,8, KW=8

Results of Analysis FEC/P-ARQ FEC (receiver) FEC (sender) original RLM

Issues for Further Investigation Estimation of channel condition Accommodation for join/leave latency Clustering of channels Study of aggregate (social) behavior Implementation

Summary FEC & Pseudo-ARQ allow error control when flow control alone is insufficient Layered (rate-compatible) FEC allows receiver-driven approach Pseudo-ARQ is more effective than FEC and uses only standard multicast machinery Hybrid FEC/Pseudo-ARQ enhances scalability Many issues remain for further investigation