RSM4CPS: The 1st International Workshop on Real-Time Stream Analytics and Machine Learning for Cyber-Physical Systems (RSM4CPS-2018) |
Website | https://sites.google.com/view/rsm4cps/home |
Submission link | https://easychair.org/conferences/?conf=rsm4cps |
Submission deadline | October 22, 2017 |
Acceptance Notification | November 15, 2017 |
Camera Ready and Registration Due: | December 1, 2017 |
The 1st International Workshop on Real-Time Stream Analytics and Machine Learning for Cyber-Physical Systems (RSM4CPS-2018) is focused on Cyber Physical Systems (CPSs) that are built around various services and applications which are deployed on the top of sensors and actuators, communication topologies and variety of computing platforms. Connection among these components creates multiple end-to-end task chains which need to work under resource constrained environments. CPSs have ability to adapt and to learn. CPSs continuously analyze their environment. They learn patterns and correlations among various instances/events based on their observations about the environment. Identifying these correlations and patterns, they tend to build significant predictive models. Applications of CPSs are in multiple domains ranging from condition monitoring and maintenance to image processing and diagnosis. In CPSs, the tight coupling between physical and computation processes has resulted in production of large volumes of data. Machine Learning (ML) techniques can significantly collaborate with CPSs to carry out monitoring and control to minimize the latency between control message reception and decision making. Traditionally used model-based ML techniques with CPSs design are unable to handle and model the complexity of extremely larger and dynamic CPSs which is the demand of current era so that they may respond in real time as well as adapt to the changing environment. Thus, current CPSs capture, analyze and learn from infinitely coming streaming data for real time decision making. Emerging distributed frameworks, computing architectures, models and algorithms that leverage infinite stream computing fit well in fulfilling above mentioned requirements. Moreover, multiple open sourced technologies in this domain may help to design even complex CPSs in a robust and cost-effective manner.
This workshop will help in capturing inherent challenges and opportunities associated with real-time stream analytics and machine learning with respect to CPS. Focus of the workshop is in exploring the state of art technologies involved in real time analytics of infinite scale streaming data in context of CPSs. Multi-dimensional aspects of distributed real time analytics and learning for wide range of applications such as healthcare, transportation, energy sector, and other domains will be evaluated in order to extract pros and cons along with futuristic advancements that is in progress or may be incorporated to enable large scale real-time and adaptive stream analytics and learning in CPSs. Overall goal of the workshop is to provide an inter-disciplinary open forum for academia and industry to exchange the knowledge and research experience on recent advancements in field of Cyber Physical System design equipped with real time stream analytics and learning in a robust, reliable and cost-effective manner.
Submission Guidelines and Publication
Papers should be at most 6 double-column pages (excluding references), including title, abstract, figures and references, and not published or under review elsewhere. Papers should be prepared as per ACM conference proceedings format (please see http://www.acm.org/sigs/publications/proceedings-templates#aL1). Please submit your papers through EasyChair (https://easychair.org/conferences/?conf=rsm4cps). All accepted workshop papers will be included in the ACM Digital library.
At least one of each accepted paper must register for the conference and present the paper. In addition, no-shows of accepted papers at the workshop will result in those papers NOT being included in the proceedings.
List of Topics
Topics of interests include but are not limited to the following areas related to CPSs
- Distributed data ingestion frameworks and tools
- Distributed data storage architectures
- Distributed data integration models and techniques
- Semantic stream processing in dynamic environments
- Distributed stream computing architectures and frameworks
- Stream learning algorithms
- Spatio-Temporal stream modeling techniques
- Self-adaptive modeling for CPSs
- Programming models for real time Cyber Physical Systems
- Evolving algorithms for real time CPSs
- Real time analytics in healthcare, aeronautics, transportation, energy, medical and other Cyber Physical Systems
- Real time machine learning and Societal Cyber Physical Systems
- IoT and Geo-Distributed real time analytics
- Cloud based real time analytics for CPS
- Stability, Safety, Reliability in real time Cyber Physical Systems
- Security and Privacy modeling in CPS
- Security risk analysis, evaluation and management
Committees
Program Committee
- Mr. Bakshi Rohit Prasad, Indian Institute of Information Technology Allahabad, India
- Mr. Swapnil Dubey, Schlumberger, India
- Dr. Vinayak Naik, Indian Institute of Information Technology Delhi, India
- Dr. Sayan Ranu, Indian Institute of Technology Delhi, India
- Dr. Rahul Kala, Indian Institute of Information Technology Allahabad, India
- Dr. M.Tanveer, Indian Institute of Technology Indore, India
- Dr. Amrita Chaturvedi, Indian Institute of Technology BHU, Varanasi, India
- Prof. Sharma Chakravarthy, University of Texas at Arlington, USA
- Prof. Dharmendra Singh, Indian Institute of Technology Roorkee, India
- Dr. Durga Toshniwal, Indian Institute of Technology Roorkee, India
- Dr. Ruwan Ranaweera, University of Peradeniya, Sri Lanka
Organizing committee
- Dr. Sonali Agarwal, Indian Institute of Information Technology Allahabad, India
- Dr. Ravi Saini, CSIR - Central Electronics Engineering Research Institute, Rajasthan, India
- Dr. Sanjay Singh, CSIR - Central Electronics Engineering Research Institute, Rajasthan, India
Venue
The workshop will be held on the Campus of IIT BHU Varanasi.
Venue
Annie Besant Lecture Theater (ABLT)
Indian Institute of Technology (BHU)
Varanasi (Uttar Pradesh)- 221005
India
Contact
All questions about submissions should be emailed to sonali@iiita.ac.in