ACM SIGCOMM 2018 Workshop on Network Meets AI & ML (NetAI 2018)

Workshop Program

8:30 am - 8:50 am Opening

Session Chair: Marco Canini (KAUST, KSA), Chen Tian (NJU, CHINA)

Location: InterContinental
Opening

8:50 am - 9:40 am

Keynote I: Communication Acceleration for Machine Learning Systems: A Case Study

Chuanxiong Guo (ByteDance, China)

9:40 am - 10:30 am Session I: Systems
Session I: Systems

9:40 am - 10:05 am

HiPS: Hierarchical Parameter Synchronization in Large-Scale Distributed Machine Learning

Jinkun Geng, Dan Li, Yang Cheng, Shuai Wang, Junfeng Li (Tsinghua University, China)

10:05 am - 10:30 am

DeepConfig: Automating Data Center Network Topologies Management with Machine Learning

Saim Salman (Brown University, USA), Chris Streiffer (Duke University, USA), Huan Chen (UESTC, China), Theophilus Benson (Brown University, USA), Asim Kadav (NEC Labs, USA)

10:30 am - 11:00 am Tea/Coffee Break (InterContinental Pre-Function Area)
Tea/Coffee Break

11:00 am - 11:50 am

Keynote II: Self-Programming Network

Balaji Prabhakar (Stanford, USA)

11:50 am - 12:40 pm Session II: Measurements I

Location: InterContinental
Session II: Measurements I

11:50 am - 12:15 pm

Empowering Sketches with Machine Learning for Network Measurements

Tong Yang, Lun Wang (Peking University, China), Yulong Shen (Xidian University, China), Muhammad Shahzad (North Carolina State University, USA), Qun Huang (Institute of Computing Technology, Chinese Academy of Sciences, China), Xiaohong Jiang (Future University of Hakodate, Japan), Kun Tan (Huawei Technologies, China), Xiaoming Li (Peking University, China)

12:15 pm - 12:40 pm

Efficient Distribution-Derived Features for High-Speed Encrypted Flow Classification

Johan Garcia (Karlstad University, Sweden), Topi Korhonen (Karlstad University, Sweden)

2:00 pm - 3:15 pm Session III: Mobility

Location: InterContinental
Session III: Mobility

2:00 pm - 2:25 pm

Adaptive Multiple Non-negative Matrix Factorization for Temporal Link Prediction in Dynamic Networks

Kai Lei, Meng Qin (Peking University, China), Bo Bai, Gong Zhang (Huawei Technologies, Hong Kong)

2:25 pm - 2:50 pm

Tracking Groups in Mobile Network Traces

Kun Tu (University of Massachusetts Amherst, USA), Bruno Ribeiro (Purdue University, USA), Ananthram Swami (Army Research Lab, USA), Don Towsley (University of Massachusetts Amherst, USA)

2:50 pm - 3:15 pm

Wireless Optimisation via Convex Bandits: Unlicensed LTE/WiFi Coexistence

Cristina Cano (Universitat Oberta de Catalunya, Spain), Gergely Neu (Universitat Pompeu Fabra, Spain)

3:15 pm - 3:45 pm Tea/Coffee Break (InterContinental Pre-Function Area)
Tea/Coffee Break
3:45 pm - 5:00 pm Session IV: Caching, Forwarding and TCP

Location: InterContinental
Session IV: Caching, Forwarding and TCP

3:45 pm - 4:10 pm

DeepCache: A Deep Learning Based Framework For Content Caching

Arvind Narayanan, Saurabh Verma, Eman Ramadan, Pariya Babaie, Zhi-Li Zhang (University of Minnesota, USA)

4:10 pm - 4:35 pm

IFS-RL: An Intelligent Forwarding Strategy Based on Reinforcement Learning in Named-Data Networking

Yi Zhang (Peking University, China), Bo Bai (Huawei Technologies, Hong Kong), Kuai Xu (Arizona State University, USA), Kai Lei (Peking University, China)

4:35 pm - 5:00 pm

Improving TCP Congestion Control with Machine Intelligence

Yiming Kong (Georgia Institute of Technology, USA), Hui Zang (FutureWei Technologies, USA), Xiaoli Ma (Georgia Institute of Technology, USA)

5:00 pm - 5:05 pm Mini-Break (InterContinental Pre-Function Area)
Mini-Break
5:05 pm - 5:55 pm Session V: Measurements II

Location: InterContinental
Session V: Measurements II

5:05 pm - 5:30 pm

Deep-Q: Traffic-driven QoS Inference using Deep Generative Network

Shihan Xiao, Dongdong He, Zhibo Gong (Huawei Technologies, China)

5:30 pm - 5:55 pm

Assessing the Impact of Network Events with User Feedback

Shobha Venkataraman, Jia Wang (AT&T Labs – Research, USA)

Overview

Distributed processing systems for Artificial Intelligence (AI) and Machine Learning (ML), such as Hadoop, Spark, Storm, GraphLab, TensorFlow etc., are widely used by industry. On the one hand, networking is a well-known bottleneck for AI & ML systems. For example, traffic patterns experienced by ML applications during training can be optimized using techniques such as parameter servers and vertex-cut for graphs. New technologies are also being embedded in the network; examples include RDMA over converged Ethernet (RoCE) and GPU direct. On the other hand, the ever increasing complexity of networks makes effective monitoring, modeling, auditing, and overall control of network traffic difficult if not impossible. Hence there is a need for more powerful methods to solve the challenges faced in network design, deployment, and management. AI & ML have been successfully applied to various perceptual domains, including computer vision, natural language processing, and voice recognition. In addition, ML techniques are showing impressive results in new domains such as medicine, finance and astronomy, to name a few. This success in non-perceptual domains suggests that ML techniques could be successfully applied to problems in the network space. The networking community should look upon all these challenges as their opportunities in the Machine Learning era.

Call for Papers

NetAI 2018 provides a venue for presenting innovative ideas to discuss future research agendas in computer networking of/by/for AI & ML systems. We look for submissions of previously unpublished work on topics including, but not limited to, the following:

telemetry in DC
network measurement
closed loop control
AI & ML algorithm for network scheduling and control
self learning network architecture and system
services identify with AI & ML
traffic engineer with AI & ML
congestion control based on AI & ML
network security based on AI & ML
network verification
network QoS based on AI & ML
measurement and analysis of network traffic for AI & ML systems
optimizing AI & ML systems with new networking options (e.g., RDMA, NVLink)
AI & ML application-driven networking optimization (e.g., MPI offload)
networking AI & ML computation with large-scale storage technologies (e.g., NVMe over Fabric, FCoE)
networking for distributed ML systems
networking for large-scale distributed graph processing systems
new network functionality for AI & ML system ( e.g., computation in network )
application-driven network architecture design

Keynotes

Balaji Prabhakar

Stanford, USA
Chuanxiong Guo

ByteDance, China

Submission Instructions

Submission implies the willingness of at least one author to attend the workshop and present the paper. Accepted papers will be included in the ACM SIGCOMM conference proceedings. Workshop organizers reserve the right to exclude a paper from distribution after the workshop if the paper is not presented at the conference. Submitted papers should contain original material that have not be previously published, nor currently submitted for consideration elsewhere. All submissions should be written in English, with a maximum length limit of 6 printed pages, including all the figures, references and appendices. The ACM SIGCOMM LaTeX and Microsoft Word templates, as well as related information, can be found at the ACM SIG Proceedings website.

Specifically, please note the following format requirements:

All papers submitted will be peer-reviewed (single-blind) and evaluated based on their suitability (i.e., within the workshop scope), novelty, and merit.
All papers must be submitted in Portable Document Format (PDF) electronically. Whatever text processor or formatter you use to write your paper (LaTeX, Microsoft Word, FrameMaker, etc.), please convert the output to PDF before submission.
Submissions must be limited to 6 pages, single-spaced, double-column, with each column 9.25” by 3.33”, 0.33” space between columns, use at least a 10pt font, and be correctly formatted to be printed on letter-sized (8.5” by 11”) paper. Submissions that violate the formatting requirements may not be reviewed.
We must be able to print your paper once it is submitted. Therefore, all fonts used in the paper MUST be embedded in the submitted PDF file.
The paper must be in a state where it can be printed clearly on standard black-and-white printers. Reviewers are not required to view your paper in color.

Please submit your paper via https://sigcomm18netaim.hotcrp.com/

Authors Take Note

The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to TWO WEEKS prior to the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.

Registration

Attendance of the workshop is by open registration and subject to the same registration fees and rules as all the other SIGCOMM 2018 workshops. The registrants of the workshop may freely attend any workshop on the same day.