Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
Temporal interactions of intervals in distributed systems
Journal of Computer and System Sciences
A framework for viewing atomic events in distributed computations
Theoretical Computer Science - Special issue on parallel computing
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Distributed algorithm to detect strong conjunctive predicates
Information Processing Letters
Causality-Based Predicate Detection across Space and Time
IEEE Transactions on Computers
Data-stream-based global event monitoring using pairwise interactions
Journal of Parallel and Distributed Computing
Predicate detection using event streams in ubiquitous environments
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Global state detection based on peer-to-peer interactions
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Analysis of interval-based global state detection
ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
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The complete set R of orthogonal temporal interactions between pairs of intervals, formulated by Kshemkalyani, allows the detailed specification of the manner in which intervals can be related to one another in a distributed execution. This paper presents a distributed algorithm to detect whether pre-specified interaction types between intervals at different processes hold. Specifically, for each pair of processes i and j, given a relation ri, j from the set of orthogonal relations R, this paper presents a distributed (on-line) algorithm to determine the intervals, if they exist, one from each process, such that each relation ri, j is satisfied for that (i, j) process pair. The algorithm uses O(n min(np, 4mn)) messages of size O(n) each, where n is the number of processes, m is the maximum number of messages sent by any process, and p is the maximum number of intervals at any process. The average time complexity per process is O(min(np, 4mn)), and the total space complexity across all the processes is min(4pn2 - 2np, 10mn2).