NEAC'21: The 3rd IEEE/ACM International Workshop on Network-Aware Big Data Computing Melbourne Melbourne, Australia, May 10, 2021 |
Conference website | https://neac2021.github.io/ |
Submission link | https://easychair.org/conferences/?conf=neac21 |
Abstract registration deadline | February 14, 2021 |
Submission deadline | February 14, 2021 |
Final CFP: The 3rd IEEE/ACM International Workshop on Network-Aware Big Data Computing (NEAC'21)co-located with IEEE/ACM CCGrid'21, 10th - 13th Of May, Melbourne, Australia (http://cloudbus.org/ccgrid2021/)
https://neac2021.github.io/
All accepted papers will be published in the Proceedings of the 21st IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing, published by IEEE.Regular technical papers must be prepared in IEEE conference format. Full papers are limited to 8 pages. Short papers with novel ideas up to 4 pages are highly encouraged.
Submission deadline: Feb 14th, 2021
*About NEAC*
Network communications is one of the main performance challenges for big data computing in large distributed systems such as datacenters, in terms of both communication time and energy consumption. Significant improvements have been achieved by using the state-of-the-art methods, designed in the research domains of data management (e.g., locality scheduling), data communications (e.g., flow scheduling) and network management (e.g., routing). However, almost all the techniques in their own fields just view each fields as a black box, and the additional performance gains from a co-optimization perspective have not yet been well explored. Moreover, in emerging data networks (e.g., DCNs with programmable switches or IoT networks), part of computation from end hosts can be offloaded into networks. This new paradigm can process data as it flows and have redefined the computation and communication in data processing, and thus how to optimize big data computing within the scheme becomes an interesting question.
NEAC aims to explore network-aware optimization opportunities for big data computing in distributed systems. It will bring researchers from related fields together to investigate innovative models, algorithms, architectures and systems to minimize data movement time, message traffic and energy consumption for big data computing in various network infrastructures, and consequently deliver significant performance improvements to the large-scale data analytics community.
*Topics*
NEAC seeks interesting and innovative contributions and surveys on methods and designs covering all aspects of optimization for data computing, communication, message traffic and energy consumption in different network configurations. This workshop also encourages new initiatives of building bridges between big data computing and network communications. Topics of interest include, but are not limited to:
-- All network-aware optimization techniques for big data computing in distributed environments such as data locality, task, job, flow and routing scheduling in cluster, grid, edge and cloud.
-- All data-aware network designs such as protocols, domain-specific solutions and architectures for wireless networks, software-defined networks, data center networks, peer-to-peer networks, sensor networks, and Internet of Things.
-- All application and network co-design techniques for big data computing such as performance models, algorithms, programming paradigms, architectures and systems.
*Program Committee*
-- Leandro Almeida, Federal Technological University of Parana, Brazil
-- Dick Epema, Delft University of Technology, Netherlands
-- Spyros Kotoulas, Facebook, UK
-- Jianbin Li, North China Electric Power University, Beijing, China
-- Zhuozhao Li, University of Chicago, USA
-- Cong Liu, Shandong University of Technology, China
-- Jinwei Liu, Florida A&M University, USA
-- Radu Prodan, University of Klagenfurt, Austria
-- Lukas Rupprecht, IBM Research Almaden, USA
-- Ilias Tachmazidis, University of Huddersfield, UK
-- Alexandru Uta, Leiden University, Netherlands
-- Shen Wang, University College Dublin, Ireland
-- Ying Wang, Institute of Computing Technology, CAS, China
-- Lei Yang, South China University of Technology, China
*Organizer*
-- Long Cheng, North China Electric Power University, Beijing, China
-- Zhiming Zhao, University of Amsterdam, Netherlands
*Publicity Chair*
-- Ying Mao, Fordham University, USA
-- Lianting Xue, North China Electric Power University, Beijing, China
*Publication Chair*
-- Qingzhi Liu, Wageningen University & Research, Netherlands
-- Yifeng Huang, North China Electric Power University, Beijing, China