With rapid development of social structure, generated by wide spread of Internet of Things(IoT) and advanced application of IT in social infrastructure, a vast amount of data such as sensor and device information needs to be properly managed at data centers.
Tackling the global warming issues such as reducing greenhouse gas emissions and power consumption has been a social mega-trend, and the power consumption reduction at data centers is no exception.
In our laboratory, we aim to make a positive contribution to the society by making the data center meet the strict requirements with the utilization of AI and virtualization technology; precisely constructing an optimal air conditioning system & task assignment system.
Active discussion with enterprises on a regular basis
Using raw data of real data centers
Demonstration tests using various sensors
Provision of PCs, laptops and other necessary equipment
Support for travel expenses, etc.
Regular research progress meetings
Weekly journal club in English, Machine learning study group
Other study sessions, presentation practices etc.
‘Liquid immersion cooling technology with natural convection in data center’ in Proceedings of IEEE CloudNet 2017, September 2017.
‘A Novel Automated Tiered Storage Architecture for Achieving both Cost Saving and QoE‘ in Proceedings of IEEE SC2 2018, November 2018.
‘High-Performance Sequence Analysis Engine for Shotgun Metagenomics Sequence comparison through GPU Acceleration’ in Proceedings of IEEE International Conference on Bioinformatics and Bioengineering (BIBE) 2018, October 2018.
‘Consensus Building for users with various preference’ in Proceedings of ICT Convergence 2018, October 2018.
‘Dynamic power consumption prediction and optimization of data center by using deep learning and computational ﬂuid dynamics’ in Proceedings of IEEE CloudNet 2018, October 2018.
‘A Novel Automated Cloud Storage Tiering System through Hot-Cold Data Classification’ in Proceedings of IEEE Cloud 2018, July 2018.
‘Self-Aware Workload Forecasting in Data Center Power Prediction’ in Proceedings of IEEE CCGRID 2018, May 2018.
‘Proposal of Cooling Method for HPC by Drip Feeding Cooling’ in Proceedings of ASHRAE 2018 Winter Conference, January 2018.
‘Effective Cooling of Server Boards in Data Centers by Liquid Immersion Based on Natural Convection Demonstrating PUE below 1.04’ in Proceedings of ASHRAE 2018 Winter Conference, January 2018.
‘Toward an Online Network Intrusion Detection System Based on Ensemble Learning’ IEEE International Conference on Cloud Computing 2019, July,2019.
‘Real-time workload allocation optimizer for computing systems by using deep learning' IEEE International Conference on Cloud Computing 2019, July,2019.
‘Deep Learning Approach for Pathogen Detection Through Shotgun Metagenomics Sequence Classiﬁcation’ AIME 2019 17th Conference on Artificial Intelligence in Medicine, July,2019.
‘Toward a Workload Allocation Optimizer for Power Saving in Data Centers’ IEEE International Conference on Cloud Engineering (IC2E), July,2019.
‘Feasibility Study of Liquid Immersion Technology for Cooling Network Equipment' OCP Future Technologies Symposium, May,2020
‘High-Performance Virus Detection System by using Deep Learning' IEEE WCCI 2020 Coference, July,2020.
‘A Deep Reinforcement Learning Approach for Anomaly Network Intrusion Detection System’ IEEE CloudNet 2020 (IEEE International Conference on Cloud Networking) Coference, November,2020.