Article Accepted in IEEE Transactions on Computers

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.

Anna Minaeva Successfully Defends Dissertation

Today, Anna Minaeva successfully defended her PhD dissertation entitled “Scalable Scheduling Algorithms for Embedded Systems with Real-Time Requirements” and earned the right to call herself a doctor. The reviewers were pleased with the dissertation and she confidently answered their questions.

The dissertation considers applications with real-time requirements sharing resources, such as memories, cores, and networks, in distributed systems. Scheduling this type of application subject to resource and precedence constraints, among others, while maximizing system performance is a challenging problem. Existing approaches either propose exact solutions that cannot solve industrial-sized instances or propose heuristic algorithms without validating its efficiency with optimal solutions.

The dissertation addresses this problem through a three-stage approach, corresponding to three problems with gradually increasing complexity and accuracy of the model. The four main contributions of are: 1) Comparison of three formalisms to solve the problems optimally, Integer Linear Programming (ILP), Satisfiability Modulo Theory, and Constraint Programming, along with computation time improvements. To increase the scalability of the ILP approach, an optimal approach that wraps the ILP in a branch-and-price framework is presented. 2) For each problem, a scalable and efficient heuristic algorithm is presented that decomposes the problem to decrease its computation time. 3) The efficiency of the optimal and heuristic strategies are quantitatively and qualitatively compared. 4) The practical applicability of the proposed heuristic algorithms and optimal approaches is demonstrated on case studies of real systems in both the automotive and consumer electronics domains.

I wish Anna the best of luck in her future career and hope I will have the opportunity to work with her again.

Article Accepted in Journal of Systems and Software

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.

Paper Accepted at RTAS 2015

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.