The 2nd International Workshop on Intelligent Cloud Computing and Networking (ICCN 2020)

Session ICCN-Opening

Opening Session

Conference
9:00 AM — 9:10 AM EDT
Local
Jul 6 Mon, 9:00 AM — 9:10 AM EDT

Opening Session

To Be Determined

0
This talk does not have an abstract.

Session Chair

To Be Determined

Session ICCN-S1

Session 1: Cloud Applications 1

Conference
9:10 AM — 9:50 AM EDT
Local
Jul 6 Mon, 9:10 AM — 9:50 AM EDT

Bottleneck-Aware Coflow Scheduling Without Prior Knowledge

Libin Liu and Hong Xu (City University of Hong Kong, Hong Kong); Chengxi Gao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China); Peng Wang (Huawei Theory Lab, China)

0
This talk does not have an abstract.

Revenue-Sharing based Computation-Resource Allocation for Mobile Blockchain

Yuan Wu (University of Macau, Macao); Xu Xu and Liping Qian (Zhejiang University of Technology, China); Bo Ji (Temple University, USA); Zhiguo Shi (Zhejiang University, China); Weijia Jia (University of Macau, Macao)

0
This talk does not have an abstract.

Session Chair

Yuan Wu

Session ICCN-KS1

Keynote Session 1

Conference
10:00 AM — 11:00 AM EDT
Local
Jul 6 Mon, 10:00 AM — 11:00 AM EDT

Distributed Edge Learning for Big Data Analytics: Challenges and Trends

Song Guo (The Hong Kong Polytechnic University, Hong Kong)

1
When accessing cloud-hosted modern applications, users often suffer a significant latency due to the long geo-distance to the central cloud. Edge computing thus emerges as an alternative paradigm that can reduce this latency by deploying services close to users. In this talk, we will analyze the methodology and limitations of popular approaches for supporting AI services on geo-distributed systems along the evolution from cloud computing to edge computing. In particular, we shall discuss how to deal with different sets of challenges in distributed machine learning over heterogeneous geo-distributed systems. We shall also present our recent studies on parameter-server based framework among networked collaborative edges.

Session Chair

Zhi Zhou

Session ICCN-S2

Session 2: Cloud Network

Conference
11:30 AM — 12:30 PM EDT
Local
Jul 6 Mon, 11:30 AM — 12:30 PM EDT

Edge Emergency Demand Response Control via Scheduling in Cloudlet Cluster

Zhaoyan Song, Ruiting Zhou, Shihan Zhao and Shixin Qin (Wuhan University, China); John Chi Shing Lui (Chinese University of Hong Kong, Hong Kong); Zongpeng Li (Wuhan University & University of Calgary, China)

0
This talk does not have an abstract.

MEM: A Multi-Staged Eviction Mechanism of Flowtable for Software-Defined Datacenters

Wei Feng, Wan Tang and XiMin Yang (South-Central University for Nationalities, China); Lu Liu (University of Leicester, United Kingdom (Great Britain))

2
This talk does not have an abstract.

Resource Allocation in MEC-enabled Vehicular Networks: A Deep Reinforcement Learning Approach

Guoping Tan, Huipeng Zhang and Siyuan Zhou (Hohai University, China)

0
This talk does not have an abstract.

Session Chair

Xinggong Zhang

Session ICCN-S3

Session 3: Cloud System

Conference
12:30 PM — 1:30 PM EDT
Local
Jul 6 Mon, 12:30 PM — 1:30 PM EDT

Terminator: An Efficient and Light-weight Fault Localization Framework

Yuxing Li (Tsinghua University, China); Hu Zheng, Chengqiang Huang, Ke Pei and Jinghui Li (Huawei, China); Longbo Huang (Tsinghua University, China)

0
This talk does not have an abstract.

Dynamic deployment model for large-scale compute-intensive clusters

Yunpeng Cao and Haifeng Wang (Linyi University, China); Shuqing He (Beijing University of Posts & Telecommunications, China)

0
This talk does not have an abstract.

Consistent User-Traffic Allocation and Load Balancing in Mobile Edge Caching

Lemei Huang, Sheng Cheng, Yu Guan, Xinggong Zhang and Zongming Guo (Peking University, China)

0
This talk does not have an abstract.

Session Chair

Shuaibing Lu

Session ICCN-S4

Session 4: Cloud Security

Conference
2:30 PM — 3:30 PM EDT
Local
Jul 6 Mon, 2:30 PM — 3:30 PM EDT

A Unified Federated Learning Framework for Wireless Communications: towards Privacy, Efficiency and Security

Hui Wen, Yue Wu, Chenming Yang and Hancong Duan (University of Electronic Science and Technology of China, China); Shui Yu (University of Technology Sydney, Australia)

2
This talk does not have an abstract.

Detecting and Mitigating ARP Attacks in SDN-Based Cloud Environment

Sixian Sun, Xiao Fu and Bin Luo (Nanjing University, China); Xiaojiang Du (Temple University, USA)

1
This talk does not have an abstract.

A Location-Based Path Privacy Protection Scheme in Internet of Vehicles

Haili Yu and Guangshun Li (Qufu Normal University, China); Wu Junhua (Harbin Engineering University, China); Xinrong Ren and Jiabin Cao (Qufu Normal University, China)

1
This talk does not have an abstract.

Session Chair

Wei Feng

Session ICCN-KS2

Keynote Session 2

Conference
3:30 PM — 4:30 PM EDT
Local
Jul 6 Mon, 3:30 PM — 4:30 PM EDT

Towards Bio- and Brain-Inspired Computing and Networking: Fluctuation-induced Yuragi Control and Learning Methods

Masayuki Murata (Osaka University, Japan)

1
Machine learning methods are now actively applied to the “Industry 4.0” and “smart city” for establishing a next ICT-enabled world. However, since the neural network was invented, brain science has much progressed by advancements of measurement devices including fMRI (functional Magnetic Resonance Imaging). We are now ready to develop the next-generation machine learning (or artificial intelligence) approaches. It is now proven that a most striking feature of the human brain is the ability to handle uncertainty under the dynamic environment containing noise in an effective way, instead of pursuing the optimality. Also, it accumulates “confidence” for reaching a final decision on the target task, which gives the flexibility of handling decisions against various sources of uncertainty. Furthermore, even after the human makes the decision, the environment may be changed by the decision itself. It can be viewed as a feedback control system, which must be utilized in artificial control systems.
In this talk, we first introduce the “Yuragi (meaning fluctuation in Japanese) concept.” It is a universal feature of adaptability found in the natural system, which can be observed in various biological systems including the human brain. It is formulated as the Yuragi theory as a simple canonical formula for explaining the adaptability in the natural system. Then, we move to the Yuragi control, which is an application of the Yuragi theory to handle the control system in artificial systems. We demonstrate its applicability by utilizing it in several networking systems. The Yuragi theory can be further extended as the machine learning approach by incorporating the Bayesian attractor model. It is called Yuragi learning, and we again show its application to the networking systems.

Session Chair

Ruidong Li

Session ICCN-S5

Session 5: Cloud Applications 2

Conference
5:00 PM — 6:00 PM EDT
Local
Jul 6 Mon, 5:00 PM — 6:00 PM EDT

An NFV MANO Architecture with a Resource Allocation Mechanism Based on Game Theory

David H. S. Lima (University of Coimbra & Federal Institute of Alagoas, Brazil); Andre Aquino (Federal University of Alagoas, Brazil); Marilia Curado (University of Coimbra, Portugal)

0
This talk does not have an abstract.

Transcoding for Live Streaming-based on Vehicular Fog Computing: An Actor-Critic DRL Approach

Fang Fu and Yunpeng Kang (Shanxi University, China); Zhicai Zhang and F. Richard Yu (Carleton University, Canada)

0
This talk does not have an abstract.

Detection of Temporal Communities in Mobile Social Networks

Mengni Ruan and Huan Zhou (China Three Gorges University, China); Dawei Li (Montclair State University, USA); Xuxun Liu (South China University of Technology, China); Qingyong Deng (XiangTan University, China)

0
This talk does not have an abstract.

Session Chair

Juan Fang

Session ICCN-S6

Session 6: Edge Cloud

Conference
6:00 PM — 7:20 PM EDT
Local
Jul 6 Mon, 6:00 PM — 7:20 PM EDT

Follow Me, If You Can: A Framework for Seamless Migration in Mobile Edge Cloud

Tung Doan (Technische Universität Dresden & Deutsche Telekom Chair of Communication Networks, Germany); Zhongyi Fan (Cloud Product Research & Development, Alibaba Cloud, China); Giang T. Nguyen (Technische Universität Dresden, Germany); Hani Salah (TU Dresden, Germany); Dongho You (Technische Universität Dresden & The Deutsche Telekom Chair of Communication Networks, Germany); Frank H.P. Fitzek (Technische Universität Dresden & ComNets - Communication Networks Group, Germany)

2
This talk does not have an abstract.

Joint Network Selection and Traffic Allocation in Multi-Access Edge Computing-Based Vehicular Crowdsensing

Luning Liu (BUPT, China); Luhan Wang (Beijing University of Posts and Telecommunications, China); Xiang Ming Wen (Beijing University of posts and telecommunications, China)

2
This talk does not have an abstract.

A Scheduling Strategy for Reduced Power Consumption in Mobile Edge Computing

Juan Fang, Yong Chen and Shuaibing Lu (Beijing University of Technology, China)

1
This talk does not have an abstract.

Incentive Mechanism Design for Edge-Cloud Collaboration in Mobile Crowd Sensing

Lihan Zhang and Zhuo Li (Beijing Information Science and Technology University, China); Xin Chen (Beijing Information Science & Technology University, China)

1
This talk does not have an abstract.

Session Chair

Hui Wen

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