0000000000224866

AUTHOR

Carmine Spagnuolo

0000-0002-8267-9808

showing 2 related works from this author

Work Partitioning on Parallel and Distributed Agent-Based Simulation

2017

Work partitioning is a key challenge with ap- plications in many scientific and technological fields. The problem is very well studied with a rich literature on both distributed and parallel computing architectures. In this paper we deal with the work partitioning problem for parallel and distributed agent-based simulations which aims at (i) balancing the overall load distribution, (ii) minimizing, at the same time, the communication overhead due to agents' inter-dependencies. We introduce a classification taxonomy of work partitioning strategies and present a space-based work partitioning ap- proach, based on a Quad-tree data structure, which enables to: identify a good space partitioning …

Theoretical computer scienceComputational complexity theoryComputer Networks and CommunicationsComputer scienceDistributed computingContext (language use)02 engineering and technologyParallel ComputingSynchronization (computer science)0202 electrical engineering electronic engineering information engineeringOverhead (computing)Space partitioningAgent-based simulation020203 distributed computingAgent-based simulations; D-MASON; Distributed Systems; Parallel Computing; Work partitioning; Hardware and Architecture; Computer Networks and Communications; Information SystemsFlocking (behavior)Agent-based simulations020206 networking & telecommunicationsWork partitioningData structureDistributed SystemComputer Networks and CommunicationD-MASONDistributed SystemsHardware and ArchitectureBoidsInformation Systems2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
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Social Influence Maximization in Hypergraphs

2021

This work deals with a generalization of the minimum Target Set Selection (TSS) problem, a key algorithmic question in information diffusion research due to its potential commercial value. Firstly proposed by Kempe et al., the TSS problem is based on a linear threshold diffusion model defined on an input graph with node thresholds, quantifying the hardness to influence each node. The goal is to find the smaller set of items that can influence the whole network according to the diffusion model defined. This study generalizes the TSS problem on networks characterized by many-to-many relationships modeled via hypergraphs. Specifically, we introduce a linear threshold diffusion process on such …

Hypergraphsocial networksSelection (relational algebra)Computer scienceGeneralizationScienceQC1-999hypergraphGeneral Physics and Astronomy02 engineering and technologyAstrophysicsArticlehigh-order networkSet (abstract data type)influence diffusion020204 information systems0202 electrical engineering electronic engineering information engineeringDiscrete mathematicshigh-order networks; hypergraphs; influence diffusion; social networks; target set selectionPhysicsQMaximizationQB460-466high-order networkshypergraphstarget set selectionGraph (abstract data type)020201 artificial intelligence & image processingNode (circuits)Heuristics
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