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Detecting Locally Distributed Predicates

Published:01 June 2011Publication History
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Abstract

In this article, we formalize locally distributed predicates, a concept previously introduced to address specific challenges associated with modular robotics and distributed debugging. A locally distributed predicate (LDP) is a novel construction for representing and detecting distributed properties in sparse-topology systems. Our previous work on LDPs presented empirical validation; here we show a formal model for two variants of the LDP algorithm, LDP-Basic and LDP-Snapshot, and establish performance bounds for these variants. We prove that LDP-Basic can detect strong stable predicates, that LDP-Snapshot can detect all stable predicates, and discuss their applicability to various distributed programming domains and to spatial computing in general. LDP detection in bounded-degree networks is shown to be scale-free, making the approach particularly attractive for specific topologies, even though LDPs are less efficient than snapshot algorithms in general distributed systems.

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                  cover image ACM Transactions on Autonomous and Adaptive Systems
                  ACM Transactions on Autonomous and Adaptive Systems  Volume 6, Issue 2
                  June 2011
                  106 pages
                  ISSN:1556-4665
                  EISSN:1556-4703
                  DOI:10.1145/1968513
                  Issue’s Table of Contents

                  Copyright © 2011 ACM

                  Publisher

                  Association for Computing Machinery

                  New York, NY, United States

                  Publication History

                  • Published: 1 June 2011
                  • Accepted: 1 June 2010
                  • Revised: 1 March 2010
                  • Received: 1 August 2009
                  Published in taas Volume 6, Issue 2

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