Negotiation Based Resource Allocation to Control Information Diffusion

dc.contributor.advisor Samik Basu
dc.contributor.author Nudurupati, Sai Sravanthi
dc.contributor.department Computer Science
dc.date 2018-08-11T14:40:56.000
dc.date.accessioned 2020-06-30T03:03:34Z
dc.date.available 2020-06-30T03:03:34Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2001-01-01
dc.date.issued 2017-01-01
dc.description.abstract <p>Study of diffusion or propagation of information over a network of connected entities play a vital role in understanding and analyzing the impact of such diffusion, in particular, in the context of epidemiology, and social and market sciences. Typical concerns addressed by these studies are to control the diffusion such that influence is maximally (in case of opinion propagation) or minimally (in case of infectious disease) felt across the network. Controlling diffusion requires deployment of resources and often availability of resources are socio-economically constrained. In this context, we propose an agent-based framework for resource allocation, where agents operate in a cooperative environment and each agent is responsible for identifying and validating control strategies in a network under its control. The framework considers the presence of a central controller that is responsible for negotiating with the agents and allocate resources among the agents. Such assumptions replicates real-world scenarios, particularly in controlling infection spread, where the resources are distributed by a central agency (federal govt.) and the deployment of resources are managed by a local agency (state govt.).</p> <p>If there exists an allocation that meets the requirements of all the agents, our framework is guaranteed to find one such allocation. While such allocation can be obtained in a blind search methods (such as checking the minimum number of resources required by each agent or by checking allocations between each pairs), we show that considering the responses from each agent and considering allocation among all the agents results in a “negotiation” based technique that converges to a solution faster than the brute force methods. We evaluated our framework using data publicly available from Stanford Network Analysis Project to simulate different types of networks for each agents.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/15392/
dc.identifier.articleid 6399
dc.identifier.contextkey 11051472
dc.identifier.doi https://doi.org/10.31274/etd-180810-5016
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/15392
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/29575
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/15392/Nudurupati_iastate_0097M_16322.pdf|||Fri Jan 14 20:40:09 UTC 2022
dc.subject.disciplines Computer Sciences
dc.title Negotiation Based Resource Allocation to Control Information Diffusion
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
thesis.degree.discipline Computer Science
thesis.degree.level thesis
thesis.degree.name Master of Science
File
Original bundle
Now showing 1 - 1 of 1
Name:
Nudurupati_iastate_0097M_16322.pdf
Size:
977.21 KB
Format:
Adobe Portable Document Format
Description: