BIOT 2016 - 2016 IEEE workshop on Big Data Management for the Internet of Things

The goal of this workshop is to share and discuss the most advanced researches and development studies in the area of “Big Data Management for the Internet of Things”. The workshop will gather researchers, engineers and practitioners from academia and industry who are working in this research domain. It will focus on new technical proposals and practical experiences with widely sharing the research issues that we must solve in this research domain. The workshop will provide an excellent opportunity to address the research issues and solutions in sufficient depth and breadth, and is intended to share knowledge and exchange ideas and/or actual field experiences, thereby promoting new studies and research topics in this area.
Theme of the Workshop
The “Internet of Things” has developed as a “Big Data” platform which potentially contains the seeds of services, profiles of social-phenoma, even social knowledge and intelligence. However, we have not yet found appropriate solutions for managing and use-of such Big Data. This workshop tries to discover better solutions for Big Data management, which may include (1) the systems for large-scale remote monitoring and control, (2) state-of-the-art data analysis and control schemes, (3) service design and use case identifications, (4) application-oriented systems. The workshop may also discuss basic technologies such as data models, algorithms, distributed systems, and communication protocols.
Scope of the Workshop (Call-for-Papers)
A huge number of sensors, actuators and tags are getting networked these days. This leads to the “Internet of Things”, and provides smart and intelligent services to human society. However, this now raises the next question; how should we use the “Big Data” associated to, or collected from, those things? They say that it potentially contains the seeds of services, profiles of social-phenoma, even social knowledge and intelligence. However, we have not yet found systematic solutions for managing them effectively, and we sometimes fail to extract valuable information from, or to provide advanced services with, the dataset. Thus, in this workshop, in order to discuss and discover better solutions, we welcome papers that explore service platforms (i.e., network systems, architectures, data models and algorithms) that effectively integrate “Internet of Things” and “Big Data”.
The workshop topics include, but are not limited to:
* Large-scale monitoring platforms
* Large-scale control platforms
* Data analysis and data applications
* Control schemes and decision making
* Data models and algorithms
* NoSQL data management
* Service design and use cases
* System architecture and implementation
* Communication protocols
* Distributed processing (overlays, Hadoop-based, etc.)
* Privacy management and anonymization
* Social embedding of applications
* Application case studies
* Performance, scalability, robustness
We respect the works inspired by practical studies with real world interactions because this workshop wants to input the story of real social needs or industrial requirements into the discussion. We also welcome work-in-progress papers. The length of a camera ready paper will be limited to 6 pages (IEEE Proceedings style) with up to 2 additional pages (with charges for each additional page) printed on 10-12 point fonts. Authors must follow IEEE CS Press Proceedings Author Guidelines to prepare papers. At least one of the authors of each accepted paper is required to pay full registration fee and present the paper at the workshop in person.
Program Committee
- B. Reddy Tamma (Indian Institute of Technology, India)
- Chaodit Aswakul (Chulalongkorn University, Thailand)
- Chian C. Ho (National Yunlin Univ. of Science&Tech., Taiwan)
- Eun-Seo Lee (ETRI, Korea)
- Hiroshi Mineno (Shizuoka Univ., Japan)
- Hiroyuki Inoue (Hiroshima City Univ., Japan)
- Jorge J. Ortiz (IBM T. J. Watson Research Center, USA)
- Kazuyuki Shudo (Tokyo Institute of Techinology, Japan)
- Kiran Kuchi (Indian Institute of Technology, India)
- Liu Xiaohan (Chinese Academy of Science, China)
- Nearchos Paspallis (Univ. of Central Lancashire, Cyprus)
- Manish Signh (Indian Institute of Technology, India)
- Masahiro Ishiyama (Toshiba Corporate R&D Center, Japan)
- Masato Yamanouchi (Keio University, Japan)
- Masayuki Hirafuji (NARC and Univ. of Tsukuba, Japan)
- Michiharu Takemoto (NTT, Japan)
- P. Rajalakshmi (Indian Institute of Technology, India)
- Romain Rouvoy (University Lille 1 and INRIA, France)
- Satoshi Matsuura (Tokyo Institute of Technology, Japan)
- Sy-Yen Kuo (National Taiwan University, Taiwan)
- Sho Fujita (Yokogawa Corporation, Japan)
- Shuai Gao (Beijing Jaotong University, China)
- Takaaki Moriya (NTT, Japan)
- Tomoki Yoshihisa (Osaka Univ., Japan)
- Yuuichi Teranishi (NICT/Osaka Univ., Japan)
- Yuusuke Kawakita (Univ. of Electro Comm., Japan)