Exact and heuristic algorithms for Space Information Flow
Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a h...
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| Published in | PloS one Vol. 13; no. 3; p. e0193350 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
27.03.2018
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0193350 |
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| Abstract | Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm. |
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| AbstractList | Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N [greater than or equal to] 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm. Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space , such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N ( N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm. Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm.Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm. |
| Audience | Academic |
| Author | Huang, Jiaqing Cheng, Wenqing Uwitonze, Alfred Li, Zongpeng Ye, Yuanqing |
| AuthorAffiliation | 4 Department of Computer Science, University of Calgary, Calgary, Canada 1 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China 2 College of Science and Technology, University of Rwanda, Kigali, P. O. BOX 3900, Rwanda 3 Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America Universidad Nacional de Mar del Plata, ARGENTINA |
| AuthorAffiliation_xml | – name: 1 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China – name: 3 Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America – name: Universidad Nacional de Mar del Plata, ARGENTINA – name: 2 College of Science and Technology, University of Rwanda, Kigali, P. O. BOX 3900, Rwanda – name: 4 Department of Computer Science, University of Calgary, Calgary, Canada |
| Author_xml | – sequence: 1 givenname: Alfred surname: Uwitonze fullname: Uwitonze, Alfred – sequence: 2 givenname: Jiaqing surname: Huang fullname: Huang, Jiaqing – sequence: 3 givenname: Yuanqing surname: Ye fullname: Ye, Yuanqing – sequence: 4 givenname: Wenqing surname: Cheng fullname: Cheng, Wenqing – sequence: 5 givenname: Zongpeng surname: Li fullname: Li, Zongpeng |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29584729$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1109/TIT.2006.874515 10.1007/978-981-10-3969-0_29 10.3390/s17040902 10.1109/49.12889 10.1109/INFCOM.2007.35 10.1109/TIT.2014.2308998 10.1002/(SICI)1097-0037(199710)30:3<149::AID-NET1>3.0.CO;2-L 10.1109/ISIT.2012.6283071 10.1002/j.1538-7305.1957.tb01515.x 10.1007/978-3-319-66628-0_45 10.1057/jors.1990.166 10.1109/TIT.2005.864435 10.1371/journal.pone.0069844 10.1109/18.850663 10.1016/0012-365X(93)E0183-5 10.1002/net.3230110104 10.1371/journal.pone.0148725 10.1137/0116001 10.1109/GLOCOM.2014.7037014 10.1109/ITW.2004.1405308 10.1109/TIT.2011.2173720 10.1109/GLOCOMW.2016.7848807 10.1109/ISIT.2012.6283627 10.1109/NetCod.2013.6570816 10.1145/290179.290180 |
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| Copyright | COPYRIGHT 2018 Public Library of Science 2018 Uwitonze et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2018 Uwitonze et al 2018 Uwitonze et al |
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| Snippet | Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms... Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space , such as Euclidean space. The design of... |
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| SubjectTerms | Algorithms Biology and Life Sciences Butterflies Coding Complexity Computation Computer and Information Sciences Computer applications Computer networks Computer simulation Decision trees Delaunay triangulation Design Euclidean geometry Flow rates Heuristic Heuristic methods Information flow Information technology Information theory International conferences Linear programming Mathematical research Multicast Multicasting Nodes Physical Sciences Problems Research and Analysis Methods Telecommunications transmission technologies Topology Triangulation Wireless networks |
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| Title | Exact and heuristic algorithms for Space Information Flow |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/29584729 https://www.proquest.com/docview/2019025704 https://www.proquest.com/docview/2019469551 https://pubmed.ncbi.nlm.nih.gov/PMC5870950 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0193350&type=printable https://doaj.org/article/76952b28e8fd4ccdb18ad2c038f327f8 http://dx.doi.org/10.1371/journal.pone.0193350 |
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