2018 Fiscal Year Annual Research Report
Research on Algorithms for Network Interdiction Problem
| Project/Area Number |
17F17727
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
塩浦 昭義 東京工業大学, 工学院, 准教授 (10296882)
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| Co-Investigator(Kenkyū-buntansha) |
BAFFIER JEAN-FRANCOIS 東京工業大学, 工学院, 外国人特別研究員
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| Project Period (FY) |
2017-10-13 – 2020-03-31
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| Keywords | network / flow / graph / algorithm |
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| Outline of Annual Research Achievements |
Our research achievements for this year are mainly focused on overcoming the difficulties foreseen at the start of this research in the computation of metrics of influence in information networks. Along with the theoretical foundations of this research, we are developing, as open-source softwares, the first libraries to solves practically those problems. Previously, two major problems were encountered that are common to all the network considered, one being the size of available data and the other the presence of cycles and strongly connected components in real life networks. Finally, the last problem to arise to practically compute those metrics in real life networks is the temporality of the transmission of knowledge.
We extended the notion of Stream Graphs ---that represents the temporality of networks using a combination of signal theory and graph theory--- to the notion of Stream Flow. With the goal to eventually apply it to our information networks, we proved classical flow notions in a stream graph context such as max-flow/min-cut duality, tractable algorithms for continuous signal functions.
With the aim to improve the computation of classical algorithm to explore graphs and search spaces, we work on general technique to reduce dimension (i.e. the number of variables and/or constraints) for general constraint optimisation problems (known as COP in the literature). Classical linear constraints are reduced accurately through the use of the Johnson-Lindenstrauss lemma (JLL). General constraints are reduced in a similar fashion after being formulated as a SAT problem.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
国内外の研究者との共同研究により，想定していた研究成果に加え，幾つかの興味深い結果を得ることが出来た．その結果，７本の論文を現在執筆中であり，幾つかについては近々投稿予定である．
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| Strategy for Future Research Activity |
Finalization and evaluation of afore-mentioned achievements, if not already available and publications of the associated library as open-source software: flow of knowledge on PDAG and general acyclic networks; general black-box algorithm for compressed data structure such as stacks, deques, lists and graphs; stream graph and flow algorithms (including visualisation tools).
Completion of the Network Interdiction framework for classical network flow using various optimization techniques adapted to small and large networks.
Extension of this framework to the flow of knowledge in information networks with the aim of discover weak links and possible fake news, in particular in dynamic environment.
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