The Role of Gossiping in Information Dissemination over a Network of Agents
We consider information dissemination over a network of gossiping agents. In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and <i>n</i> receiver nodes want to follow the information at the source as accurately as possible. When...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/26/1/9 |
| _version_ | 1827372372805550080 |
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| author | Melih Bastopcu Seyed Rasoul Etesami Tamer Başar |
| author_facet | Melih Bastopcu Seyed Rasoul Etesami Tamer Başar |
| author_sort | Melih Bastopcu |
| collection | DOAJ |
| description | We consider information dissemination over a network of gossiping agents. In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and <i>n</i> receiver nodes want to follow the information at the source as accurately as possible. When the information at the source changes, the source first sends updates to a subset of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>m</mi><mo>≤</mo><mi>n</mi></mrow></semantics></math></inline-formula> nodes. Then, the nodes share their local information during the <i>gossiping period</i>, to disseminate the information further. The nodes then estimate the information at the source, using the majority rule at the end of the gossiping period. To analyze the information dissemination, we introduce a new error metric to find the average percentage of nodes that can accurately obtain the most up-to-date information at the source. We characterize the equations necessary to obtain the steady-state distribution for the average error and then analyze the system behavior under both high and low gossip rates. We develop an adaptive policy that the source can use to determine its current transmission capacity <i>m</i> based on its past transmission rates and the accuracy of the information at the nodes. Finally, we implement a clustered gossiping network model, to further improve the information dissemination. |
| first_indexed | 2024-03-08T10:57:42Z |
| format | Article |
| id | doaj.art-dc7e8f06260b4171942b9f3bc14676b8 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-08T10:57:42Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-dc7e8f06260b4171942b9f3bc14676b82024-01-26T16:22:47ZengMDPI AGEntropy1099-43002023-12-01261910.3390/e26010009The Role of Gossiping in Information Dissemination over a Network of AgentsMelih Bastopcu0Seyed Rasoul Etesami1Tamer Başar2Coordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, IL 61801, USACoordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, IL 61801, USACoordinated Science Laboratory, University of Illinois Urbana-Champaign, Urbana, IL 61801, USAWe consider information dissemination over a network of gossiping agents. In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and <i>n</i> receiver nodes want to follow the information at the source as accurately as possible. When the information at the source changes, the source first sends updates to a subset of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>m</mi><mo>≤</mo><mi>n</mi></mrow></semantics></math></inline-formula> nodes. Then, the nodes share their local information during the <i>gossiping period</i>, to disseminate the information further. The nodes then estimate the information at the source, using the majority rule at the end of the gossiping period. To analyze the information dissemination, we introduce a new error metric to find the average percentage of nodes that can accurately obtain the most up-to-date information at the source. We characterize the equations necessary to obtain the steady-state distribution for the average error and then analyze the system behavior under both high and low gossip rates. We develop an adaptive policy that the source can use to determine its current transmission capacity <i>m</i> based on its past transmission rates and the accuracy of the information at the nodes. Finally, we implement a clustered gossiping network model, to further improve the information dissemination.https://www.mdpi.com/1099-4300/26/1/9information disseminationgossip networksgossiping effectsocial networksMarkov chains |
| spellingShingle | Melih Bastopcu Seyed Rasoul Etesami Tamer Başar The Role of Gossiping in Information Dissemination over a Network of Agents Entropy information dissemination gossip networks gossiping effect social networks Markov chains |
| title | The Role of Gossiping in Information Dissemination over a Network of Agents |
| title_full | The Role of Gossiping in Information Dissemination over a Network of Agents |
| title_fullStr | The Role of Gossiping in Information Dissemination over a Network of Agents |
| title_full_unstemmed | The Role of Gossiping in Information Dissemination over a Network of Agents |
| title_short | The Role of Gossiping in Information Dissemination over a Network of Agents |
| title_sort | role of gossiping in information dissemination over a network of agents |
| topic | information dissemination gossip networks gossiping effect social networks Markov chains |
| url | https://www.mdpi.com/1099-4300/26/1/9 |
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