SWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocol

Several distributed peer-to-peer applications require weakly-consistent knowledge of process group membership information at all participating processes. SWIM is a generic software module that offers this service for largescale process groups. The SWIM effort is motivated by the unscalability of traditional heart-beating protocols, which either impose network loads that grow quadratically with group size, or compromise response times or false positive frequency w.r.t. detecting process crashes. This paper reports on the design, implementation and performance of the SWIM sub-system on a large cluster of commodity PCs. Unlike traditional heartbeating protocols, SWIM separates the failure detection and membership update dissemination functionalities of the membership protocol. Processes are monitored through an efficient peer-to-peer periodic randomized probing protocol. Both the expected time to first detection of each process failure, and the expected message load per member, do not vary with group size. Information about membership changes, such as process joins, drop-outs and failures, is propagated via piggybacking on ping messages and acknowledgments. This results in a robust and fast infection style (also epidemic or gossipstyle) of dissemination. The rate of false failure detections in the SWIM system is reduced by modifying the protocol to allow group members to suspect a process before declaring it as failed this allows the system to discover and rectify false failure detections. Finally, the protocol guarantees a deterministic time bound to detect failures. Experimental results from the SWIM prototype are presented. We discuss the extensibility of the design to a WANwide scale. Author last names are in alphabetical order. The authors were supported in part by NSF CISE grant 9703470, in part by DARPA/AFRLIFGA grant F30602-99-1-0532, and in part by a grant under NASA’s REE program, administered by JPL.