Project: RoseLine

Name: RoseLine

TItle: Enabling Robust, Secure and Efficient Knowledge of Time Across the System Stack

Description: This is a collaborative project funded by the National Science Foundation under its Cyber-Physical Systems program, and involves researchers from CMU, UCLA, UCSB, UCSD, and the University of Utah. Accurate and reliable knowledge of time is fundamental to cyber-physical systems for sensing, control, performance, and energy efficient integration of computing and communications. This simple statement underlies the RoseLine project. Emerging CPS applications depend on precise knowledge of time to infer location and control communication. There is a diversity of semantics used to describe time, and quality of time varies as we move up and down the system stack. System designs tend to overcompensate for these uncertainties and the result is systems that may be over designed, in-efficient, and fragile. The intellectual merit derives from the new and fundamental concept of time and the holistic measure of quality of time (QoT) that captures metrics including resolution, accuracy, and stability. The project has built a system stack that enables new ways for clock hardware, OS, network services, and applications to learn, maintain and exchange information about time, influence component behavior, and robustly adapt to dynamic QoT requirements, as well as to benign and adversarial changes in operating conditions. Robust and tunable quality of time has applicability across a broad spectrum of applications that pervade modern life. Example application areas that benefit from Quality of Time include: smart grid, networked and coordinated control of aerospace systems, underwater sensing, and industrial automation. The project is also providing valuable opportunities to integrate research and education in graduate, undergraduate, and K-12 via publications, open sourcing of software, and participation in activities such as the Los Angeles Computing Circle for pre-college students.

Status: Active Project

Main Research Area: Pervasive Computing

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