1. Communication algorithms with advice
- Author
-
Pierre Fraigniaud, Andrzej Pelc, David Ilcinkas, Laboratoire d'informatique Algorithmique : Fondements et Applications (LIAFA), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Algorithmics for computationally intensive applications over wide scale distributed platforms (CEPAGE), Université Sciences et Technologies - Bordeaux 1 (UB)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Département d'Informatique et d'Ingénierie (DII), Université du Québec en Outaouais (UQO), See paper for details., ANR-07-BLAN-0322,ALADDIN,Algorithm Design and Analysis for Implicitly and Incompletely Defined Interaction Networks(2007), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), and Université Sciences et Technologies - Bordeaux 1-Inria Bordeaux - Sud-Ouest
- Subjects
Computer Networks and Communications ,Distributed computing ,Message complexity ,Network ,0102 computer and information sciences ,02 engineering and technology ,Broadcasting ,01 natural sciences ,Graph ,Theoretical Computer Science ,0202 electrical engineering, electronic engineering, information engineering ,Size of advice ,Dissemination ,Mathematics ,Linear number ,business.industry ,Applied Mathematics ,Telecommunications network ,Algorithm ,Computational Theory and Mathematics ,010201 computation theory & mathematics ,Broadcast communication network ,Graph (abstract data type) ,020201 artificial intelligence & image processing ,[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC] ,business ,Advice (complexity) ,Wakeup - Abstract
International audience; We study the amount of knowledge about a communication network that must be given to its nodes in order to efficiently disseminate information. Our approach is {\em quantitative}: we investigate the minimum total number of bits of information (minimum size of advice) that has to be available to nodes, regardless of the type of information provided. We compare the size of advice needed to perform broadcast and wakeup (the latter is a broadcast in which nodes can transmit only after getting the source information), both using a linear number of messages (which is optimal). We show that the minimum size of advice permitting the {\em wakeup} with a linear number of messages in a $n$-node network, is $\Theta (n \log n)$, while the {\em broadcast} with a linear number of messages can be achieved with advice of size $O(n)$. We also show that the latter size of advice is almost optimal: no advice of size $o(n)$ can permit to broadcast with a linear number of messages. Thus an efficient wakeup requires strictly more information about the network than an efficient broadcast.
- Published
- 2010