Contemporarily, in light of the intelligent transportation systems (ITS) sector, the tendency can be observed that the solution of the multi-objective cyber-physical optimization problems with imperfect information takes an increasingly weighted role. In the present scientific work, the authors want to take these developments into account by introducing an innovative cyber-physical architectural design and corresponding the two-stage heuristic computing approach. It is utilized in synergy with the MCSA11Multi-tier Cyber-physical System Architecture and DCEx architectural principles for the workflow scheduling of Monte-Carlo simulation, which is based on the intelligent and sustainable route-order dispatching process model. Factors such as emissions, transport costs, risks, and the individual weighting of orders are reflected in the model. In particular, the authors define a stochastic ILP-based22Integer Linear Programming monte-carlo workflow model. They further propose two-stage scheduling heuristic with 6-HEFT DAG relaxation as first stage and apply state-of-the-art techniques as a part of SCIP framework to solve 2nd 1-0 ILP-based stage; evaluate the performance of the scheduling approach. The authors obtain preliminary results of the second stage behavior using a realistic heterogeneous computing scenario and corresponding constraint structures within MACS simulator engine33Modular Architecture for Complex Computing Systems Analysis. The results from the experiments illustrate moderate complexity of the approach. Scalability of the model looks promising for the applicability in various industry-related scenarios and corresponding computing environments.
An Innovative Control Approach for Cyber-Physical Transportation Systems: The Case of Monte-Carlo Workflow Computations
Marozzo F.;
2024-01-01
Abstract
Contemporarily, in light of the intelligent transportation systems (ITS) sector, the tendency can be observed that the solution of the multi-objective cyber-physical optimization problems with imperfect information takes an increasingly weighted role. In the present scientific work, the authors want to take these developments into account by introducing an innovative cyber-physical architectural design and corresponding the two-stage heuristic computing approach. It is utilized in synergy with the MCSA11Multi-tier Cyber-physical System Architecture and DCEx architectural principles for the workflow scheduling of Monte-Carlo simulation, which is based on the intelligent and sustainable route-order dispatching process model. Factors such as emissions, transport costs, risks, and the individual weighting of orders are reflected in the model. In particular, the authors define a stochastic ILP-based22Integer Linear Programming monte-carlo workflow model. They further propose two-stage scheduling heuristic with 6-HEFT DAG relaxation as first stage and apply state-of-the-art techniques as a part of SCIP framework to solve 2nd 1-0 ILP-based stage; evaluate the performance of the scheduling approach. The authors obtain preliminary results of the second stage behavior using a realistic heterogeneous computing scenario and corresponding constraint structures within MACS simulator engine33Modular Architecture for Complex Computing Systems Analysis. The results from the experiments illustrate moderate complexity of the approach. Scalability of the model looks promising for the applicability in various industry-related scenarios and corresponding computing environments.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
