Optimality-Guaranteed Design Space Pruning for CAN-FD Frame Packing

With the development of the automotive industry toward intelligence and automation, there is a trend of controller area network (CAN) migrating to CAN with flexible data-rate (CAN-FD), where frame packing (i.e., packing signals of various periods, deadlines, and payloads into frames following the standard CAN-FD format) is critical to address the high bandwidth demand with limited resources. Existing works have applied integer linear programming (ILP), which easily gets intractable as the number of signals to be packed increases, or proposed heuristics, which are not able to obtain the optimal solution. In addition, the security model employed does not meet the AUTOSAR SecOC specification. This article reports a novel frame-packing approach for CAN-FD with an AUTOSAR-compliant security model. We establish the theory that extending the existing frame to pack signals with the same period leads to shorter worst-case transmission time (WCTT) and thus lower bus utilization compared to creating a new frame. Following this principle, the design space is tremendously pruned, where the optimal solution is guaranteed to remain. With pruning, we are able to increase the optimally solvable size of the problem from 150 signals to 300 signals, which is sufficient for practical usage. When there are 300 signals, only 10-142 of the original design space needs to be explored. To further improve efficiency, we apply pruning to heuristics. When the signal size is 500, for simulated annealing (SA), the computation time can be reduced by 54.1% and the bus utilization can be saved by 10.5% with pruning being deployed. In addition, we propose the max-min ant system as an alternative, which achieves better bus utilization than SA in shorter computation. Our reported method is generally applicable to other CAN-based distributed networks demanding higher bandwidth as well, such as in industry automation.