Model-based implementation of real-time applications

Abstract

Correct and efficient implementation of general real-time applications remains by far an open problem. A key issue is meeting timing constraints whose satisfaction depends on features of the execution platform, in particular its speed. Existing rigorous implementation techniques are applicable to specific classes of systems e.g. with periodic tasks, time deterministic systems.We present a general model-based implementation method for real-time systems based on the use of two models.• An abstract model representing the behavior of real-time software as a timed automaton. The latter describes user-defined platform-independent timing constraints. Its transitions are timeless and correspond to the execution of statements of the real-time software. • A physical model representing the behavior of the realtime software running on a given platform. It is obtained by assigning execution times to the transitions of the abstract model.A necessary condition for implementability is time-safety, that is, any (timed) execution sequence of the physical model is also an execution sequence of the abstract model. Timesafety simply means that the platform is fast enough to meet the timing requirements. As execution times of actions are not known exactly, time-safety is checked for worst-case execution times of actions by making an assumption of timerobustness: time-safety is preserved when speed of the execution platform increases. We show that as a rule, physical models are not timerobust and show that time-determinism is a sufficient condition for time-robustness.For given real-time software and execution platform corresponding to a time-robust model, we define an Execution Engine that coordinates the execution of the application software so as to meet its timing constraints. Furthermore, in case of non-robustness, the Execution Engine can detect violations of time-safety and stop execution.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. EMSOFT'10, October 24-29, 2010, Scottsdale, Arizona, USA. Copyright 2010 ACM 978-1-60558-904-6/10/10 ...$10.00.We have implemented the Execution Engine for BIP programs with real-time constraints. We have validated the implementation method for an adaptive MPEG video encoder. Experimental results reveal the existence of timing anomalies seriously degrading performance for increasing platform execution speed.

Rigorous implementation of real-time systems – from theory to application

“…The current paper extends our previous work presented in Abdellatif et al (2010), and is structured as follows:…”

Optimized distributed implementation of multiparty interactions with Restriction

“…It also includes generating distributed models with timing constraints as in [1]. In particular, the multi-threaded implementation in [46], where all timing constraints are handled by a single thread, could be extended to a fully distributed implementation.…”

Automated addition of fault recovery to cyber-physical component-based models

“…Priorities are used for scheduling purposes. Automated transformations for BIP have successfully been used to generate real-time [1] as well as distributed [5,6] code that is correct-by-construction. In [4], the authors address deadlock detection in BIP models, but the approach falls short on resolving deadlock states (e.g., created due to the occurrence of faults).…”

“…We first define a generic fault model and the notion of fault recovery for component-based models. Then, we identify two sets of constraints on addition of fault recovery to cyber-physical models: (1) constraints to guarantee that adding recovery mechanism does not interfere with the normal behavior of the model in the absence of faults (i.e., conditions on preserving the correctness of the original model in the absence of faults), and (2) constraints to ensure that cyber-physical characteristics of the model are respected during addition of recovery to the original model. One example of latter constraints is that the recovery mechanism is not allowed to alter the internal structure of physical components.…”