| Project/Area Number |
19K20216
|
|---|
| Research Category |
Grant-in-Aid for Early-Career Scientists
|
| Allocation Type | Multi-year Fund |
|---|
| Review Section |
Basic Section 60010:Theory of informatics-related
|
|---|
| Research Institution | Japan Advanced Institute of Science and Technology (2020-2021)
National Institute of Informatics (2019) |
|---|
Principal Investigator |
Schwartzman Gregory 北陸先端科学技術大学院大学, 先端科学技術研究科, 准教授 (20815261)
|
|---|
| Project Period (FY) |
2019-04-01 – 2022-03-31
|
| Project Status |
Completed (Fiscal Year 2021)
|
| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2019: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
|
|---|
| Keywords | Graph algorithms / Distributed algorithms / Smoothed analysis / Dynamic networks / Distributed computing / Approximation algorithms / Algorithms / Approximation / Distributed / Streaming |
|---|
| Outline of Research at the Start |
The goal of this research is to advance the understanding of fundamental algorithms for environments with uncertainty, namely, the distributed and streaming environments. We achieve this by focusing on approximation algorithms for fundamental combinatorial optimization problems.
|
| Outline of Final Research Achievements |
The goal of this research is to advance the understanding of fundamental algorithms for environments with uncertainty, namely, the distributed environment. We achieve this by presenting novel algorithms for fundamental graph problems (e.g,. combinatorial optimization, graph detection).
Furthermore, we show novel algorithms for the dynamic distributed setting which better captures real world systems. Finally, we go beyond worst-case analysis and consider the smoothed-complexity of fundamental problems in the dynamic distributed setting.
|
| Academic Significance and Societal Importance of the Research Achievements |
We present new distributed algorithms for fundamental problems in the distributed setting. As many modern real world systems have a distributed aspect to them, our algorithm can be used to improve their performance of this systems in the future, and provide theoretical understanding in the present.
|
