6533b7d7fe1ef96bd1267cce

RESEARCH PRODUCT

A New Universal-Environment Adaptive Multi-processor Scheduler for Autonomous Cyber-Physical System

Zhou LuYuan YaoXiao WuKailong ZhangOuassila Labanni

subject

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation020203 distributed computingComputer sciencebusiness.industryQuality of serviceDistributed computing[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Cyber-physical systemMultiprocessing02 engineering and technologyMulti processor[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationFuzzy logicScheduling (computing)Knowledge-based systemsEmbedded system0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Robot[INFO.INFO-ES]Computer Science [cs]/Embedded Systems020201 artificial intelligence & image processing[ INFO.INFO-ES ] Computer Science [cs]/Embedded Systemsbusiness

description

International audience; Robot, spaceship and other applications that can be called autonomous Cyber-Physical Systems (CPS) are all smart embedded systems, which usually run in open environment by themselves with inhered intelligent capabilities. Besides the application intelligence, the researches of adaptive platform for such systems have also become topics recently. Based on the analysis of current work, a new environment adaptive scheduler (¦Á-S) for multiprocessor platform of a cyber-physical system is proposed in this article. And then, its related structures, models, and reasoning methods are studied deeply. Different from the existing ones, ¦Á-S can schedule all tasks according to the environment change by two layered functions. The upper one uses not only the properties of a task but also the state of environment and system resources as input variables, which is defined as Universal Environment (UE), and then calculates the Quality of Scheduling of all tasks with a customized fuzzy logic. The lower one allocates these tasks onto processors automatically under the dynamic performance evaluation of computing resources, such as load and success rate of each processor. Further, some allocation policies are studied and defined to make ¦Á-S be more flexible to adapt different requirements. Finally, studied methods are simulated and then experimented on an obstacle-avoiding robot system.

https://doi.org/10.1109/icis.2012.9