DocumentCode :
2723774
Title :
Local Distributed Decision
Author :
Fraigniaud, Pierre ; Korman, Amos ; Peleg, David
Author_Institution :
Univ. Paris Diderot, Paris, France
fYear :
2011
fDate :
22-25 Oct. 2011
Firstpage :
708
Lastpage :
717
Abstract :
A central theme in distributed network algorithms concerns understanding and coping with the issue of locality. Despite considerable progress, research efforts in this direction have not yet resulted in a solid basis in the form of a fundamental computational complexity theory for locality. Inspired by sequential complexity theory, we focus on a complexity theory for distributed decision problems. In the context of locality, solving a decision problem requires the processors to independently inspect their local neighborhoods and then collectively decide whether a given global input instance belongs to some specified language. We consider the standard LOCAL model of computation and define LD(t) (for local decision) as the class of decision problems that can be solved in t communication rounds. We first study the intriguing question of whether randomization helps in local distributed computing, and to what extent. Specifically, we define the corresponding randomized class BPLD(t,p,q), containing all languages for which there exists a randomized algorithm that runs in t rounds, accepts correct instances with probability at least p and rejects incorrect ones with probability at least q. We show that p2+q = 1 is a threshold for the containment of LD(t) in BPLD(t,p,q). More precisely, we show that there exists a language that does not belong to LD(t) for any t=o(n) but does belong to BPLD(0,p,q) for any p,q ∈ (0,1] such that p2+q≤1. On the other hand, we show that, restricted to hereditary languages, BPLD(t,p,q) = LD(O(t)), for any function t and any p,q ∈ (0,1] such that p2+q>;1. In addition, we investigate the impact of non-determinism on local decision, and establish some structural results inspired by classical computational complexity theory. Specifically, we show that non-determinism does help, but that this help is limited, as there exist languages that cannot be decided non-deterministically. Perhaps su- prisingly, it turns out that it is the combination of randomization with non-determinism that enables to decide all languages in constant time. Finally, we introduce the notion of local reduction, and establish some completeness results.
Keywords :
computational complexity; distributed algorithms; probability; computational complexity theory; distributed network algorithms; hereditary languages; local distributed decision; probability; randomized algorithm; sequential complexity theory; Computational complexity; Computational modeling; Context; Distributed algorithms; Distributed computing; Program processors; local decision; local distributed algorithms; nondeterminism; oracles; randomized algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Foundations of Computer Science (FOCS), 2011 IEEE 52nd Annual Symposium on
Conference_Location :
Palm Springs, CA
ISSN :
0272-5428
Print_ISBN :
978-1-4577-1843-4
Type :
conf
DOI :
10.1109/FOCS.2011.17
Filename :
6108235
Link To Document :
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