0000000000224865

AUTHOR

Gennaro Cordasco

0000-0001-9148-9769

showing 3 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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Whom to befriend to influence people

2020

Alice wants to join a new social network, and influence its members to adopt a new product or idea. Each person $v$ in the network has a certain threshold $t(v)$ for {\em activation}, i.e adoption of the product or idea. If $v$ has at least $t(v)$ activated neighbors, then $v$ will also become activated. If Alice wants to activate the entire social network, whom should she befriend? More generally, we study the problem of finding the minimum number of links that a set of external influencers should form to people in the network, in order to activate the entire social network. This {\em Minimum Links} Problem has applications in viral marketing and the study of epidemics. Its solution can be…

FOS: Computer and information sciencesPhysics - Physics and SocietyGeneral Computer ScienceFOS: Physical sciencesPhysics and Society (physics.soc-ph)0102 computer and information sciences02 engineering and technology01 natural sciencesSocial networksGraphTheoretical Computer ScienceCombinatoricsComputer Science - Data Structures and AlgorithmsGreedy algorithmFOS: Mathematics0202 electrical engineering electronic engineering information engineeringMathematics - CombinatoricsData Structures and Algorithms (cs.DS)Greedy algorithmTime complexityNP-completeMathematicsSocial and Information Networks (cs.SI)Social networkDiscrete mathematicsBinary treeDegree (graph theory)Computer Science (all)Order (ring theory)Computer Science - Social and Information NetworksJoin (topology)Influence maximizationGreedy algorithms010201 computation theory & mathematicsGraphs; Greedy algorithms; Influence maximization; NP-complete; Social networksProduct (mathematics)020201 artificial intelligence & image processingCombinatorics (math.CO)Constant (mathematics)GraphsTheoretical Computer Science
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