报告内容摘要：

 

In the design of time-critical applications, schedulability analysis is used to define the feasibility region of tasks with deadlines, so that optimization techniques can find the best design solution within the timing constraints. The formulation of the feasibility region based on the response time calculation requires many integer variables and is too complex for solvers. Approximation techniques have been used to define a convex subset of the feasibility region, used in conjunction with a branch and bound approach to compute suboptimal solutions for optimal task period selection, priority assignment, or placement of tasks onto CPUs

In this talk, we provide an improved and simpler real-time schedulability test that allows an exact and efficient definition of the feasibility region in Mixed Integer Linear Programming (MILP) optimization. Our method requires a significantly smaller number of binary variables and is viable for the treatment of industrial-size problem.

 

报告人简介：

Haibo Zeng is currently with Department of Electrical & Computer Engineering at McGill University, Canada, and will join Virginia Tech in August 2014. He received the Ph.D. in Electrical Engineering and Computer Sciences from University of California at Berkeley, the B.E. and M.E. in Electrical Engineering from Tsinghua University, Beijing, China. He was a senior researcher at General Motors R&D until October 2011. His research interests are design methodology, analysis, and optimization for embedded systems, cyber-physical systems, and real-time systems. He has authored or co-authored over 50 papers in the above fields. He was the recipient of three Best Paper Awards.

 

 

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