Efficient detection of a class of stable properties

Summary We present a general protocol for detecting whether a property holds in a distributed system, where the property is a member of a class of stable properties we call thelocally stable properties. Our protocol is based on a decentralized method for constructing a maximal subset of the local states that are mutually consistent, which in turn is based on a weakened version of vector time stamps. The structure of our protocol lends itself to refinement, and we demonstrate its utility by deriving some specialized property-detection protocols, including two previously-known protocols that are known to be efficient. Laura Sabel received the BSE degree from Princeton University in 1989 and the MS degree in Computer Science from Cornell University in 1992. She is currently a PhD student in the Department of Computer Science at Cornell University. Her research interests include fault-tolerance and distributed systems. she is the recipient of an AT&T PhD Scholarship. Keith Marzullo received his Ph.D. degree in electrical engineering from Stanford University in 1984. He is an associate professor in the Computer Science and Engineering Department at the University of California, San Diego. His research interests are in the area of fault-tolerance in both asynchronous and real-time distributed systems. He has consulted on several projects including the IBM Air Traffic Control System, and is an associate editor for IEEE Transactions on Software Engineering.This work was supported by the Defense Advanced Research Projects Agency (DoD) under NASA Ames grant number NAG 2-593, and by grants from IBM and Siemens. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official Department of Defense position, policy, or decision. An earlier version of this paper appears in theProceedings of the 5th International Workshop on Distributed Systems, October 1991, Springer-Verlag LNCS Vol. 579This author is also supported by an AT&T PhD Scholarship