The last decade has witnessed a rapid evolution of IT infrastructures. Cloud computing has become the norm of computing with a large number of huge data centers deployed all over the globe. With the fast development of new communication technologies such as 5G, LoRa, or LiFi, cloud computing is now evolving into yet another new paradigm called edge computing, providing better support for emerging applications, especially in the Internet-of-Things regime.
Extensive research has been carried out on system design and optimization for improving the performance of the IT infrastructure. However, most of them put their focus on performance metrics including latency, throughput, reliability, and even security. Yet, another important facet – energy efficiency of the IT infrastructure - has received limited attention in the literature. With the increase of the scale of the IT infrastructure, energy efficiency becomes more relevant and calls for more attention. In fact, while there is relevant literature in the study of energy efficiency in cloud and data centers, there is very limited work on the energy impact of edge computing and systems (both in isolation and integrated with clouds).
Many energy efficiency related research problems exist and will become a major obstacle to the development of future computing and communication systems involving the edge. Therefore, the proposed workshop aims to bring together academic researchers, industry practitioners, and individuals working on related areas to share their research ideas, views, latest findings, and state-of-the-art research results. We welcome prospective authors to submit their articles on topics including, but not limited to the following.
Title: Lightweight Short-term Photovoltaic Power Prediction for Edge Computing
Speaker: Albert Zomaya (University of Sydney)
Abstract: To meet the needs for energy savings in Internet of Things (IoT) systems, solar energy has been increasingly exploited to serve as a green and renewable source to allow systems to better operate in an energy-efficient way. In this respect, accurate photovoltaics (PV) power output prediction is a prerequisite for any energy saving scheme employed in these systems. In this talk, I am going to discuss a unified training framework combined with the LightGBM algorithm to obtain a prediction model, which can provide short-term predictions of PV power output. Compared with the training in a single powerful machine, our proposed framework is more energy-efficient and fits into devices with limited computation and storage capabilities. The experimental results show that our proposed framework is superior to other benchmark machine learning algorithms.
Bio: Albert Y. ZOMAYA is currently the Chair Professor of High Performance Computing & Networking in the School of Computer Science, University of Sydney. He is also the Director of the Centre for Distributed and High Performance Computing. He published more than 600 scientific papers and articles and is author, co-author or editor of more than 25 books. He is the Founding Editor in Chief of the IEEE Transactions on Sustainable Computing and the Editor in Chief of the ACM Computing Surveys and previously he served as Editor in Chief for the IEEE Transactions on Computers (2011-2014). He delivered more than 190 keynote addresses, invited seminars, and media briefings and has been actively involved, in a variety of capacities, in the organization of more than 700 conferences. Professor Zomaya is the recipient of many awards, such as, the IEEE Computer Society Technical Achievement Award (2014), the ACM MSWIM Reginald A. Fessenden Award (2017), and the New South Wales Premier’s Prize of Excellence in Engineering and Information and Communications Technology (2019). He is a Chartered Engineer, a Fellow of AAAS, IEEE, IET (UK), an Elected Member of Academia Europaea, and an IEEE Computer Society’s Golden Core member. Professor Zomaya’s research interests lie in parallel and distributed computing, networking, and complex systems.
|Los Angeles (PDT)||Edmonton (MDT)||New York (EDT)||London (BST)||Paris (CEST)||Beijing (CST)||Tokyo (JST)||Melbourne (AEST)|
|Opening||Jun 25, 23:00||Jun 26, 00:00||Jun 26, 02:00||Jun 26, 07:00||Jun 26, 08:00||Jun 26, 14:00||Jun 26, 15:00||Jun 26, 16:00|
|Keynote||Jun 25, 23:05||Jun 26, 00:05||Jun 26, 02:05||Jun 26, 07:05||Jun 26, 08:05||Jun 26, 14:05||Jun 26, 15:05||Jun 26, 16:05|
|Break||Jun 26, 00:05||Jun 26, 01:05||Jun 26, 03:05||Jun 26, 08:05||Jun 26, 09:05||Jun 26, 15:05||Jun 26, 16:05||Jun 26, 17:05|
|Paper 1||Jun 26, 00:15||Jun 26, 01:15||Jun 26, 03:15||Jun 26, 08:15||Jun 26, 09:15||Jun 26, 15:15||Jun 26, 16:15||Jun 26, 17:15|
|Paper 2||Jun 26, 00:35||Jun 26, 01:35||Jun 26, 03:35||Jun 26, 08:35||Jun 26, 09:35||Jun 26, 15:35||Jun 26, 16:35||Jun 26, 17:35|
|Paper 3||Jun 26, 00:55||Jun 26, 01:55||Jun 26, 03:55||Jun 26, 08:55||Jun 26, 09:55||Jun 26, 15:55||Jun 26, 16:55||Jun 26, 17:55|
|Break||Jun 26, 01:15||Jun 26, 02:15||Jun 26, 04:15||Jun 26, 09:15||Jun 26, 10:15||Jun 26, 16:15||Jun 26, 17:15||Jun 26, 18:15|
|Paper 4||Jun 26, 01:30||Jun 26, 02:30||Jun 26, 04:30||Jun 26, 09:30||Jun 26, 10:30||Jun 26, 16:30||Jun 26, 17:30||Jun 26, 18:30|
|Paper 5||Jun 26, 01:50||Jun 26, 02:50||Jun 26, 04:50||Jun 26, 09:50||Jun 26, 10:50||Jun 26, 16:50||Jun 26, 17:50||Jun 26, 18:50|
|Paper 6||Jun 26, 02:10||Jun 26, 03:10||Jun 26, 05:10||Jun 26, 10:10||Jun 26, 11:10||Jun 26, 17:10||Jun 26, 18:10||Jun 26, 19:10|
|Closing||Jun 26, 02:30||Jun 26, 03:30||Jun 26, 05:30||Jun 26, 10:30||Jun 26, 11:30||Jun 26, 17:30||Jun 26, 18:30||Jun 26, 19:30|
Albert Zomaya (University of Sydney)
[Paper 1] Time Series Anomaly Detection Based on Language Model
Weixia Dang, Biyu Zhou, Weigang Zhang, Songlin Hu (Institute of Information Engineering, Chinese Academy of Sciences)
[Paper 2] X-Leep: Leveraging Cross-Layer Pacing for Energy-Efficient Edge Systems
Stefan Reif (Friedrich-Alexander University Erlangen-Nürnberg (FAU)), Benedict Herzog (Friedrich-Alexander-University Erlangen-Nürnberg (FAU)), Pablo Gil Pereira, Andreas Schmidt (Saarland Informatics Campus), Tobias Büttner, Timo Hönig, Wolfgang Schröder-Preikschat (Friedrich-Alexander-University Erlangen-Nürnberg (FAU)), Thorsten Herfet (Saarland Informatics Campus)
[Paper 3] Explicitly Consider Server-Attached Fans for Thermal Modeling in Edge Data Centers
Xu Zhao, Yijun Lu, Zhan Li, Jian Tan, Youquan Feng, Yuan Tao (Alibaba Cloud)
[Paper 4] A Lightweight Energy-Efficient Computational Offloading Scheme in Mobile Edge Computing
Weigang Zhang, Biyu Zhou, Weixia Dang, Songlin Hu (Institute of Information Engineering, Chinese Academy of Sciences)
[Paper 5] Eco-friendly Dynamic Task Scheduling for Regional Data Center
Avinab Marahatta, Ce Chi, Kaixuan Ji, Fa Zhang (University of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences), Carlos Juiz (University of the Balearic Islands), Zhiyong Liu (University of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences)
[Paper 6] PriorityBucket: A Multipath-QUIC Scheduler on Accelerating First Rendering Time in Page Loading
Xiang Shi, Fa Zhang, Zhiyong Liu (Institute of Computing Technology, Chinese Academy of Sciences)
We invite submissions of up to 6 pages in length (including references), formatted using standard 9-point ACM double-column format (sigconf proceedings template), single-blind. Papers that do not meet the size and formatting requirements may not be reviewed. Word and LaTeX templates are available on the ACM Publications Website. All papers must be original and not simultaneously submitted to another journal or conference. All accepted workshop papers will be published along with the e-Energy proceedings and will be available via the ACM Digital Library. Selected papers from WEEE 2020 will be invited to a Special Issue of Energies.