This paper discusses detection of global predicates in a distributed program. Earlier algorithms for detection of global predicates proposed by Chandy and Lamport work only for stable predicates. A predicate is stable if it does not turn false once it becomes true. Our algorithms detect even unstable predicates, without excessive overhead. In the past, such predicates have been regarded as too difficult to detect. The predicates are specified by using a logic described formally in this paper. We discuss detection of weak conjunctive predicates that are formed by conjunction of predicates local to processes in the system. Our detection methods will detect whether such a predicate is true for any interleaving of events in the system, regardless of whether the predicate is stable. Also, any predicate that can be reduced to a set of weak conjunctive predicates is detectable. This class of predicates captures many global predicates that are of interest to a programmer. The message complexity of our algorithm is bounded by the number of messages used by the program. The main applications of our results are in debugging and testing of distributed programs. Our algorithms have been incorporated in a distributed debugger that runs on a network of Sun workstations in UNIX.
We show that the problem of predicate detection in distributed systems is NP-complete. In the past, efficient algorithms have been developed for special classes of predicates such as stable predicates, observer-independent predicates, and conjunctive predicates. We introduce a class of predicates, semi-linear predicates, which properly contains all of the above classes. We first discuss stable, observer-independent and semi-linear classes of predicates and their relationships with each other. We also study closure properties of these classes with respect to conjunction and disjunction. Finally, we discuss algorithms for detection of predicates in these classes. We provide a non-deterministic, detection algorithm for each class of predicate. We show that each class can be equivalently characterized by the degree of non-determinism present in the algorithm. Stable predicates are defined as those that can be detected by an algorithm with the most nondeterminism. All other classes can be derived by appropriately constraining the non-determinism in this algorithm.keywords: distributed debugging, predicate detection, unstable predicates.£ A preliminary version of this
Consider a network of n processes each of which has a d-dimensional vector of reals as its input. Each process can communicate directly with all the processes in the system; thus the communication network is a complete graph. All the communication channels are reliable and FIFO (first-in-first-out). The problem of Byzantine vector consensus (BVC) requires agreement on a d-dimensional vector that is in the convex hull of the d-dimensional input vectors at the non-faulty processes. We obtain the following results for Byzantine vector consensus in complete graphs while tolerating up to f Byzantine failures:• We prove that in a synchronous system, n ≥ max( 3f +1, (d+1)f +1 ) is necessary and sufficient for achieving Byzantine vector consensus. *
This paper discusses detection of global predicates in a distributed program. A run of a distributed program results in a set of sequential traces, one for each process. These traces may be combined to form many global sequences consistent with the single run of the program. A strong global predicate is true in a run if it is true for all global sequences consistent with the run. We present algorithms which detect if the given strong global predicate became true in a run of a distributed program. Our algorithms can be executed on line as well as off line. Moreover, our algorithms do not assume that underlying channels satisfy FIFO ordering.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.