The 8th International Workshop on Big Data and Cloud Performance (DCPerf'18)

Co-located with the IEEE INFOCOM'18
Honolulu, HI, USA
April 16, 2018

http://infocom2018.ieee-infocom.org/content/workshop-dcperf-big-data-and-cloud-performance

Overview

Cloud data centers are the backbone infrastructure for tomorrow's information technology. Their advantages are efficient resource provisioning and low operational costs for supporting a wide range of computing needs, be it in business, scientific or mobile/pervasive environments. Because of the rapid growth in user-defined and user-generated applications and content, the range of services provided at data centers will expand tremendously and unpredictably. Particularly, big data applications and services, e.g., social and environmental sensing, and IoT monitoring, present a unique class of challenges in the Cloud. In addition, the high volume of mixed workloads and the diversity of services offered render the performance optimization of data centers even more challenging. Moreover, important optimization criteria, such as scalability, reliability, manageability, power efficiency, area density, and operating costs, are often conflicting. The increasing mobility of users across geographically distributed areas adds another dimension to optimizing big data and cloud applications.

The goal of this workshop is to promote a community-wide discussion to identify suitable strategies to enable effective and scalable performance optimizations. We are looking for papers that present new techniques, introduce new methodologies, propose new research directions, or discuss strategies for resolving open performance problems for hosting big data analytics in the cloud.

Program

• 08:00 – 08:10
  Opening Remarks
  Chairs: Shaolei Ren and Juan F. Perez
  
  

• 08:10 – 09:00
  Keynote Session
  
  Speaker: Prof. Fangming Liu (Huazhong University of Science and Technology)
  Title: Shaping the Clouds from a QoSE (Quality-Open-Smart-Green) Perspective
  Abstract: Cloud computing and cloud storage upon large-scale datacenters (DCs) and content delivery networks (CDNs), are becoming the fundamental paradigm of multiplexing and managing massive computing, storage, networking and big data resources as utility, which host a wide range of Internet-scale services and applications. In this keynote, we envision a four-dimensional development trend of clouds in terms of Quality-Open-Smart-Green (QoSE), by not only exploring new design space and open source deployment of emerging cloud systems at the service-level spectrum (such as multiple inter-clouds and hybrid clouds), but also identifying challenges and opportunities of underlying DC resource management at the infrastructure-level spectrum (such as SDN/NFV-enabled DC performance guarantee and data-driven energy efficiency optimization). Concrete case studies and inspiring research results will be illustrated to bridge theory and practice, so as to foster comprehensive brainstorming and cross-disciplinary collaboration for shaping the future clouds.
  
  

• 09:00 – 10:00
  Session 1: Experimental Big Data
  Online Metrics Prediction in Monitoring Systems
  Matthieu Caneill (University of Grenoble Alpes, France); Noel De Palma (Universite de Grenoble - France, France); Ali Ait-Bachir, Bastien Dine and Rachid Mokhtari (Coservit, France); Yagmur Cinar (University of Grenoble Alpes, France)
  
  Empirical Study on Taxi's Mobility Nature in Dense Urban Area
  Zhenkun Qiu (University of Science and Techonology of China, P.R. China); Sihai Zhang and Wuyang Zhou (University of Science and Technology of China, P.R. China); Shui Yu (Deakin University, Australia)
  
  Available Bandwidth Estimation in Public Clouds
  Phuong Ha and Lisong Xu (University of Nebraska-Lincoln, USA)
  
  

• 10:00 – 10:30
  Coffee break
  
  

• 10:30 – 12:00
  Session 2: Distributed Transactions and Scheduling in the Cloud
  Building Efficient and Available Distributed Transaction with Paxos-based Coding Consensus
  Shenglong Li, Quanlu Zhang, Zhi Yang, Hanyu Zhao and Yafei Dai (Peking University, P.R. China)
  
  AQM with Multi-queue for Microburst in Data Center Networks
  Wataru Morita, Daisuke Sugahara, Kouji Hirata and Miki Yamamoto (Kansai University, Japan)
  
  Stochastic Non-preemptive Co-flow Scheduling with Time-Indexed Relaxation
  Ruijiu Mao, Vaneet Aggarwal and Mung Chiang (Purdue University, USA)
  
  Trade-off between Fairness and Efficiency in Dominant alpha-fairness Family
  Youngmi Jin (KDDI Reserach, Inc, Japan); Michiaki Hayashi (KDDI Research Inc., Japan)
  

Organizing Committee

TPC co-Chairs

Shaolei Ren, University of California, Riverside, USA
Juan F. Perez, Universidad del Rosario, Colombia

TPC Members (continuously updating)

Roberto Bruschi, University of Genoa, Italy
Luca Chiaraviglio, University of Rome Tor Vergata, Italy
Waltenegus Dargie, TU Dresden, Germany
Esa Hyytia, University of Iceland, Iceland
Samee U. Khan, North Dakota State University/NSF, USA
Samuel Kounev, University of Wurzburg, Germany
Chao Li, Shanghai Jiao Tong University, China
Fangming Liu, Huazhong University of Science and Technology, China
Zhenhua Liu, Stony Brook University, USA
Ningfang Mi, Northeastern University, USA
Nguyen H. Tran, Kyung Hee University, Korea
Bhuvan Urgaonkar, Penn State University, USA
Florian Wamser, University of Wurzburg, Germany
Kui Wu, University of Victoria, Canada
Jianguo Yao, Shanghai Jiao Tong University, China

Steering Committee

Jiannong Cao, Hong Kong Polytechnic University, Hong Kong
Alok Choudhary, Northwerstern University, USA
Peter Muller, IBM Research Zurich Lab, Switzerland
Martin Schmatz, IBM Research Zurich Lab, Switzerland
Anand Sivasubramaniam, Penn State University, USA
Larry Xue, Arizona State University, USA

Topics of Interest (include but are not limited to)

• Big data applications and services

  • Emerging IoT applications

  • Data flow management

  • Processing platforms

  • Empirical studies

• Cloud systems

  • Novel architectures

  • Resource allocation

  • Content distribution

  • Evaluation/modeling methodology

• Big data and cloud performance

  • Cost/pricing design

  • Power/energy management

  • Reliability/dependability

  • Performance evaluation/modeling

• Big data in the cloud

  • Intra/Inter communication

  • Network protocols

  • Security

  • Real-time analytics

Important Dates

• Paper Registration and Submission: January 13, 2018

• Notification of Acceptance: February 7, 2018

• Final Manuscript Due: March 1, 2018

• Workshop Date: April 16, 2018

Submission Guideline

Manuscripts must be limited to 6 pages in IEEE 8.5x11-inch format. Accepted papers will be published in the combined INFOCOM 2018 Workshop proceedings and will be submitted to IEEE Xplore. Submitted papers may not have been previously published in or be under consideration for publication in another journal or conference. The reviews will be single blinded. Manuscripts should be submitted as PDF files via EDAS.