Minimizing the makespan of diagnostic multi-query graphs in embedded real time systems

In recent years numerous control systems were deployed with safety-critical components comprised of real time embedded systems. These systems have electronic control units connected by networks, sensors and actuators. These systems demand high levels of reliability and have strict timing constraints especially in case of fault occurrence. One method to achieve this reliability is to introduce continuous monitoring and active diagnosis in the system. For implementing the active diagnosis in real-time systems, processing of diagnostic queries needs to satisfy the strict timing bounds. Our optimization algorithms minimize the overall makespan of Diagnostic Mutli-Query Graphs (DMG) in order to meet timing bounds. The overall makespan of the DMG is minimized by applying query optimization and graph optimization techniques. Query optimization is applied to the Fault Diagnostic Queries (FDQs) that are the part of each node of the DMG. The best access methods and best query execution plans are selected for the optimization of FDQs. The graph optimization is also applied to our DMG without affecting the semantics of FDQs. The proposed techniques are tested with different types of parameters including (i). FDQs, (ii). Left Deep Tree (LDT) and Bushy Tree (BT) and (iii) network topologies. The proposed techniques are tested in the context of two domains including (i) vehicles and (ii) Heating Ventilation and Air Conditioning System (HVAC). These proposed methodologies show a significant reduction of the makespan and give convincing results with different parameters.