Workshop on Edge Computing for Cyber Physical Systems

Workshop on Edge Computing for Cyber Physical Systems (CyberEdge)
in conjunction with IEEE SECON 2019
Boston, MA, USA
June 10, 2019

IMPORTANT DATES:
Paper Submission Deadline: April 5, 2019
Acceptance Notification: May 7, 2019
Camera Ready Deadline: May 17, 2019

CyberEdge will provide a forum for practitioners and researchers from diverse backgrounds to exchange and discuss their recent ideas, research achievements, design and implementation experiences within the CPS and edge computing spaces.

Edge computing within CPS is a vivid research field, with immediate impact on real life applications and products. Many research questions are still open such as the integration of edge computing facilities with energy harvesting systems and mobility prediction, e.g., to provide computation for fleets of vehicles. A fully online, flexible load balancing of computing services at the edge, while meeting all deadlines, requires further theoretical and especially experimental developments. Other aspects that are of interest are the investigation of joint physical (PHY)/channel access(MAC) and edge computing systems, especially assessing the impact of PHY/MAC protocols, how much and what kind of data should be measured given the following computing step, whether and how computation may be split between the data sources and the edge servers, e.g., computing functionality split. Other open issues are application specific, e.g., such as in visual sensor networks or user/object tracking systems, where user/object/scene detection shall be performed at the network edge to provide ultra-low latency services.

The workshop welcomes contributions on these and other aspects, a non-exhaustive list follows:
– Joint PHY/MAC and edge computing designs.
– Edge computing architectures and orchestration of computing resources.
– Integration of edge computing algorithms with energy harvesting systems.
– Edge computing for mobile/vehicular networks.
– Data storage, processing algorithms and management for CPS.
– Machine learning based approaches to edge computing within CPS.
– Application of learning and control techniques to edge computing systems.
– Economic models for edge computing in CPS.
– Security and privacy issues.

Information on paper submission is available at the workshop web site.