Effectively utilizing elastic resources in networked control systems

Automotive software implements different functionalities as multiple control applications sharing common platform resources. Although such applications are often developed independently, the control performance of the resulting system depends on how these applications are integrated. A key integration challenge is to efficiently schedule these applications on shared resources with minimal control performance degradation. We formulate this problem as that of scheduling multiple distributed periodic control tasks that communicate via messages with non-zero jitter. The optimization criterion used is a piecewise linear representation of the control performance degradation as a function of the end-to-end latency of the application. The three main contributions of this article are: 1) a constraint programming (CP) formulation to solve this integration problem optimally on time-triggered architectures, 2) an efficient heuristic called Flexi, and 3) an experimental evaluation of the scalability and efficiency of the proposed approaches. In contrast to the CP formulation, which for many real-life problems might have unacceptably long running times, Flexi returns nearly optimal results (0.5% loss in control performance compared to optimal) for most problems with more acceptable running times.

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“…With the above considerations, the equivalent sampled-data model is derived in [4] and can be written as…”

Section: Control Modelmentioning

confidence: 99%

“…The set R r is a union of time intervals, for which resource r is occupied by already scheduled activities. For the example in Figure 6, R ECU1 = {[0, 2], [4,6], [9,11], [14,15]}. It is introduced to reduce the computation time of the procedure.…”

Section: B Feasibility Stagementioning

confidence: 99%

Control Performance Optimization for Application Integration on Automotive Architectures

Minaeva

Roy

Åkesson

et al. 2021

IEEE Trans. Comput.

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“…Recently, Balszun et al [85] have proposed a control algorithm for mixed TT and best effort communication. The algorithm uses TT communication to guarantee worst case performance requirement while exploiting best effort communication to improve the performance and thereby achieving higher average performance.…”

Section: ) Using Hybrid Architecturesmentioning

confidence: 99%