Cost-effective services in distributed cloud/edge networks
Reporter: Liu Kaiyang
Report time: 2:30 pm on May 4th
Reporting location: Railway Campus No. 1 Comprehensive 226
Report Introduction: Big Data Analysis、The boom in data-intensive applications such as social networks and the Internet of Things，Places a huge burden on the underlying storage system。In order to alleviate the increasing storage pressure，The data seabet app download storage system has experienced from a single machine to a cluster composed of modular systems，The development history of large-scale distributed systems in cloud/edge networks。How to effectively operate and manage distributed systems for data-intensive applications，Has great theoretical significance and huge potential commercial value。This report will focus on data storage and caching solutions，From a system design perspective，Introducing the presenter and his team’s use of mathematical optimization、seabet mobile Machine Learning、Optimization and performance evaluation methods such as graph theory and network economics，Committed to achieving high efficiency in distributed cloud/edge networks、Low latency、Research work on real-time processing and highly scalable storage systems。
Personal introduction: Liu Kaiyang received his PhD from the School of Information Science and Engineering, Central South University in June 2019。November 2019 to April 2023，For the University of Victoria, Canada、Postdoctoral fellow at Central South seabet mobile University。Will join the Department of Computer Science at Memorial University of Newfoundland, Canada in July 2023，Served as Assistant Professor。Current research areas include cloud/edge computing and storage networks，Data Center Network，and distributed machine learning。Nominated for the IEEE LCN 2018 Best Paper Award。Won the IEEE Cloud Computing Technical Committee (TCCLD) Outstanding Doctoral Thesis Award in 2020，In recognition of its contribution to research on cost-effective services in cloud data centers。
