CoopNet: Cooperative Networking Phil Chou, Venkat Padmanabhan, Helen Wang September 17, 2002

Motivation “Flash crowd” can overwhelm server often due to news event of widespread interest… … but not always (e.g., Webcast of birthday party) can affect relatively obscure sites (e.g., election.dos.state.fl.us, firestone.com, nbaa.org) affects Web content as well as streaming content (live and on-demand) infrastructure-based CDNs aren’t for everyone Goal: solve the flash crowd problem!

Cooperative Networking Client-server Pure peer-to-peer CoopNet CoopNet complements client-server system Client-server operation in normal times P2P content distribution invoked on demand to alleviate server overload Clients participate only while interested in the content Server still plays a critical role P2P comm central to the system Us: no: Addresses problem cases of client-server communication Complements traditional client-server communications Clients cooperate to improve performance only when needed Clients may only be willing to cooperate for short periods We study CoopNet in the context of the flash crowd problem Selective use of p2p

Research Activities Web flash crowd alleviation (with Kay Sripanidkulchai) evaluation using Sep 11 traces from MSNBC prototype implementation done paper @ IPTPS ’02 MDC-based streaming media distribution evaluation using Sep 11 traces from MSNBC, Akamai, Digital Island implementation in progress paper @ NOSSDAV ’02 patent process in progress initial discussions with Digital Media Division

Research Activities (contd.) PeerMetric (with Karthik Lakshminarayanan) characterize broadband network performance P2P as well as client-server performance working with Xbox Online (Mark VanAntwerp) deployment on ~25 distributed nodes underway eventual deployment on ~300 Xbox Live beta users Future directions CoopNet in a Wireless Mesh Network good synergy: saves Internet bandwidth, improves robustness

Robustness of Live Streaming Peers are not dedicated servers  potential disruption due to: node departures and failures higher priority traffic Traditional ALM is not sufficient

Traditional Application-level Multicast

CoopNet Approach to Robustness Multiple description coding (MDC) Multiple, diverse distribution trees

Multiple Description Coding MDC Layered coding Unlike layered coding, there isn’t an ordering of the descriptions Every subset of descriptions must be decodable Modest penalty relative to layered coding

Multiple Description Coding Simple MDC: every Mth frame forms a description More sophisticated MDC combines: layered coding Reed-Solomon coding priority encoded transmission optimized bit allocation

Multiple Distribution Trees

Tree Management Goals: short and wide trees efficiency diversity quick join and leave processing scalability CoopNet approach: centralized protocol anchored at the server

Centralized Tree Management Basic protocol nodes inform server of their arrival/departure server tracks node capacity and tells new nodes where to join each node monitors its packet loss rate and takes action when the loss rate becomes too high simple, should scale to 1000+ joins/leaves per sec. Optimizations delay coordinates to estimate node proximity (à la GeoPing) achieving efficiency and diversity migrate “stable” nodes to a higher level in the tree

Achieving Efficiency and Diversity SEA NY S Supernode SF

MDC versus SDC Based on MSNBC traces from Sep 11

CoopNet Transport Architecture Embedded Stream ZSF GOF Parse Packetize Optimize (M, p(m)) RD Curve Break Points M descriptions RS Encoder Server Internet Depacketize Embedded Stream (truncated) Reformat Decode Render GOF (quality depends on # descriptions received) m≤ M descriptions RS Decoder Client

Summary Robustness is the key challenge MDC with multiple distribution trees improves robustness in peer-to-peer media streaming Centralized tree management is efficient and can scales

Current Activity CoopNet media streaming system is being built Evaluation: adaptability server scalability media stream quality overhead in MDC and control protocol Dealing with client heterogeneity combine MDC with layering

Issues Firewall and NAT traversal Digital Right Management issues ISP pricing policies Enterprise scenarios

Quality During Multiple Failures

Quality During Single Failure