Anna Minaeva, who recently received her PhD degree, just had a journal article entitled “Efficient Heuristic and Exact Approach for Control Performance Optimization in Time-Triggered Periodic Scheduling” accepted for publication in IEEE Transactions on Computers. This article is the result of a HiPEAC collaboration grant that Anna was awarded back in 2016 to visit the group of Samarjit Chakraborty at TU Munich. I am very happy to see that this grant resulted in a joint publication in a prestigious journal and hope to collaborate with Samarjit again in the future.
The article addresses the problem of generating a time-triggered schedule for a number of independently developed automotive applications on a number of shared resources, such that their control performance only suffers minimal degradation. The three main contributions are: 1) a constraint programming model that solves the problem optimally, exploiting properties of the problem to reduce the computation time; 2) a fast heuristic called Flexi that only has a minor impact on the optimality of the solution; and 3) an experimental evaluation of the scalability and efficiency of the proposed approaches on a case study, in addition to several synthetic datasets. The results show that the heuristic provides a solution on average 5 times faster, finding a feasible solution in 31% more problem instances than the optimal approach within a time limit, while only sacrificing 0.5% of the control performance quality for the largest dataset.
Congratulations to Anna Minaeva for having her article “Scalable and Efficient Configuration of Time-Division Multiplexed Resources” accepted in Journal of Systems and Software. The article is an extension of our conference paper “An Efficient Configuration Methodology for Time-Division Multiplexed Single Resources” that was presented at the Real-Time and Embedded Technology and Applications Symposium (RTAS) earlier this year. The original conference paper addresses the problem of configuring a Time-Division Multiplexing (TDM) arbiter that provides access to a single shared resource, such as a memory, in a way the satisfies the bandwidth and latency requirements of all memory clients. This is achieved using an optimized Integer Linear Programming (ILP) formulation.
The newly accepted article extends the problem scope to consider more complex system with a larger number of memory clients and a longer TDM frame. For large problems, the previous ILP formulation takes unpractically long to solve, which is addressed by using it as a building block in a Branch and Price framework to improve its scalability. This approach decomposes the problem into smaller sub-problems and uses more sophisticated exploration methods to navigate the search-space, enabling the number of clients to be increased by up to a factor of 8 compared to the original ILP formulation.
We just had a paper accepted at the Real-Time and Embedded Technology and Applications Symposium (RTAS) in Seattle. The paper is entitled “An Efficient Configuration Methodology for Time-Division Multiplexed Single Resources” and presents an ILP-based methodology to allocate TDM slots to resource clients, such that bandwidth and latency constraints are satisfied while resource utilization is minimized. A heuristic algorithm is furthermore proposed to determine the number of TDM slots in the schedule. This paper is a collaboration both with colleagues here at CTU Prague and with Andrew Nelson from Eindhoven University of Technology.
For the camera-ready version of the paper, please click here.