Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박용수 | - |
dc.date.accessioned | 2018-03-12T08:52:07Z | - |
dc.date.available | 2018-03-12T08:52:07Z | - |
dc.date.issued | 2013-07 | - |
dc.identifier.citation | SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, 권: 89, 호: 7, 페이지: 846-859 | en_US |
dc.identifier.issn | 0037-5497 | - |
dc.identifier.uri | http://journals.sagepub.com/doi/10.1177/0037549713485499 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/45606 | - |
dc.description.abstract | Distributed trigger counting (DTC) is a problem related to the detection of triggers with nodes in large-scale distributed systems that have general characteristics of complex adaptive systems. The triggers come from an external source, and no a priori information about the triggers is given. DTC algorithms can be used for distributed monitoring and global snapshots. When designing an efficient DTC algorithm, the following goals should be considered: minimizing the overall message complexity and distributing the loads for detecting triggers among nodes. In this paper, we propose a randomized algorithm called TreeFill, which satisfies the message complexity of with high probability. The maximum number of received messages to detect triggers in each node is with high probability. These results satisfy the lower bounds of DTC problems. We prove the upper bounds of TreeFill. The performance of TreeFill is also evaluated by means of an agent-based simulation using NetLogo. The simulation results show that TreeFill uses about 54-69% of the messages used in a previous work called CoinRand. The maximum number of received messages in each node of TreeFill is also smaller than that in the previous work. | en_US |
dc.description.sponsorship | This work was supported by the IT R&D program of MKE/KEIT (grant number 10043896, Development of virtual memory system on multi-server and application software to provide realtime processing of exponential transaction and high availability service), by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MEST grant number 2012R1A1A2007263), and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant number 2009-0069740). | en_US |
dc.language.iso | en | en_US |
dc.publisher | SAGE PUBLICATIONS LTD | en_US |
dc.subject | Distributed trigger counting | en_US |
dc.subject | distributed algorithm | en_US |
dc.subject | complex adaptive systems | en_US |
dc.subject | multi-agent systems | en_US |
dc.subject | randomized algorithm | en_US |
dc.subject | data aggregation | en_US |
dc.subject | distributed systems | en_US |
dc.title | An optimal distributed trigger counting algorithm for large-scale networked systems | en_US |
dc.type | Article | en_US |
dc.relation.no | 7 | - |
dc.relation.volume | 89 | - |
dc.identifier.doi | 10.1177/0037549713485499 | - |
dc.relation.page | 846-859 | - |
dc.relation.journal | SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL | - |
dc.contributor.googleauthor | Kim, Seokhyun | - |
dc.contributor.googleauthor | Lee, Jaeheung | - |
dc.contributor.googleauthor | Park, Yongsu | - |
dc.contributor.googleauthor | Cho, Yookun | - |
dc.relation.code | 2013007880 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF COMPUTER SCIENCE | - |
dc.identifier.pid | yongsu | - |
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