2/1/00 Porcupine: a highly scalable service Authors: Y. Saito, B. N. Bershad and H. M. Levy This presentation by: Pratik Mukhopadhyay CSE 291 Presentation on Full citation: Yasushi Saito, Brian N. Bershad, and Henry M. Levy. "Manageability, Availability and Performance in Porcupine: A Highly Scalable Cluster-based Mail Service." Proceedings of the 17th ACM Symposium on Operating Systems Principles, December 1999.

2/1/00 Goals of Porcupine High Performance : must handle billions of messages Good Scalability : must scale to 100’s of nodes, yet have competitive single node performance High Availability : must mask node failures from users Easy System Administration

2/1/00 System Architecture Functionally homogeneous nodes Key processes : membership manager mailbox manager, user profile manager replication manager mail delivery proxy (SMTP) mail retrieval proxy (POP & IMAP)

2/1/00 Terminology Mailbox fragment Mailbox fragment list User profile database User profile soft state User map Cluster membership list

2/1/00 System Management Desired features : Transparent handling of node addition, deletion and temporary node failures Load balancing across nodes automatically in face of changing workloads

2/1/00 Membership services Uses a variant of Three Round Membership Protocol Failure detection methods: remote operation timeout ping neighbor in IP address order periodically broadcast probe packets periodically Is broadcasting a good idea ? Allowing any node to be a coordinator ?

2/1/00 Recovery process User map reconstruction Soft state reconstruction -- A 2 step process : + Find changes + Notify changes Cache soft state information ? Do we reconfigure after every failure ?

2/1/00 Scaling Easy addition of new nodes : just install software and connect to network ( make IP address known to users ) Performance studies show that the system uses the newly available resources

2/1/00 Replication Basic properties : update anywhere eventual consistency total updates no locking ordered by loosely synchronized clocks Relaxed consistency for the user database ?

2/1/00 Load balancing Collecting load information : + side effect of RPC operations + load information packets Limit spread of a users mail for better performance

2/1/00 Conclusions Performance studies show that Porcupine is scalable, highly available and makes good use of resources under all workloads.

2/1/00 Miscellaneous Functional homogeneity -- good or bad ? Will it work for stuff other than ? For a very large system do we want a single geographical presence ? Special support for mailing list mail ?