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A decentralized deterministic information propagation model for robust communication

  • SUNY Buffalo
  • Air Force Research Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Many of the methods that are used to optimize network structure for information sharing are centralized, which is not always desirable in practice. Often, it is only feasible to have the communicating actors modify the network locally, i.e., without relying on the knowledge of the entire network structure. Such a requirement typically arises in establishing communication between actors (e.g., Unmanned Aerial Vehicles) that either do not have access to a central hub or prefer not to use this direct transmission channel even if available. This paper adopts an actor-oriented modeling approach to develop the Decentralized Deterministic Information Propagation (DDIP) model that enables the creation of networks that exhibit the properties desirable for efficient information sharing. Computational experiments showcase the ability of the DDIP model to form robust networks while being energy-conscious, i.e., without unnecessarily overloading any particular actor.

Original languageEnglish
Title of host publicationComputational Data and Social Networks - 7th International Conference, CSoNet 2018, Proceedings
EditorsMy T. Thai, Xuemin Chen, Wei Wayne Li, Arunabha Sen
PublisherSpringer Verlag
Pages235-246
Number of pages12
ISBN (Print)9783030046477
DOIs
StatePublished - 2018
Event7th International Conference on Computational Data and Social Networks, CSoNet 2018 - Shanghai, China
Duration: Dec 18 2018Dec 20 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11280 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Computational Data and Social Networks, CSoNet 2018
Country/TerritoryChina
CityShanghai
Period12/18/1812/20/18

Keywords

  • Communication networks
  • Decentralized optimization
  • Stochastic actor-oriented modeling

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