| Project/Area Number |
16K16053
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Information network
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| Research Institution | Kitami Institute of Technology (2017)
National Institute of Information and Communications Technology (2016) |
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Principal Investigator |
SHAO XUN 北見工業大学, 工学部, 特任助教 (80774588)
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| Project Period (FY) |
2016-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | IoT / Overlay Networks / Big data / Distributed Systems / ICN / Big Data / Edge Computing / IoT (Internet of Things) / big data / in-network processing / overlay / CCN/NFN / Hybrid Cloud / Internet of Things (IoT) / Content Centric Network / Next Generation Overlay |
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| Outline of Final Research Achievements |
In recent years, big data processing for IoT has become more and more important. In conventional big data processing system, data from distributed sensing resources has to be transported to data centers to be processed. Such centralized model suffers from expensive network cost and long waiting time. In this research, I work on the framework and key algorithms to enable big data processing by the cooperation of distributed edge computing resources. Specifically, I propose an overlay network-based distributed big data processing architecture that takes the advantages of the cooperation of edge computing resources. To overcome the inherent problems in alleviating flash crowds and handling biased workloads, I propose novel flash crowds alleviation algorithm and load balancing algorithm. The algorithms are verified with intrinsic analysis and extensive experiments. The above achievements are expected to stimulate further development of IoT services.
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