121637
20190331192655.0
doi
10.1109/RTCSA.2006.42|
CONF
Mapping task-graphs on distributed ECU networks: Efficient algorithms for feasibility and optimality
2006
2006
Conference Papers
This mapping problem has to be solved in many application scenarios. In the automotive industry, for example, the implementation of car functions involves distributed task sets running on multiple electronic control units (ECU) with bus-based inter-task communication, a problem we consider in this paper. Our approach is based on mixed integer linear programming (MILP). MILP is concerned with optimizing a linear function subject to a set of linear constraints where some variables are required to be integer. The current state-of-the art method to solve integer programs is the branch-and-cut (B&C) algorithm and several industrial strength solvers are available. We describe a MILP-model for the mapping problem. Handling this model over to a general MILP-solver does not yield satisfactory results in terms of running time. To make the model more efficient we use the above ingredients: we incorporate a primal heuristic, strengthen the model with further inequalities and generate on-demand cutting planes, which violate the current fractional solution. These routines drastically speed up the solution time
Damm, Werner
Metzner, Alexander
240331
Eisenbrand, Friedrich
183121
Shmonin, Gennady
Wilhelm, Reinhard
Winkel, Sebastian
87-90
Proceedings - 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2006
252111
DISOPT
U11879
oai:infoscience.tind.io:121637
conf
SB
DISOPT-CONF-2006-001
073110721878/DISOPT
OTHER
PUBLISHED
CONF