E. A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Invited paper to Annals of Software Engineering, Special Volume on Real-Time Software Engineering, Volume 7, 1999.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....actors, which do not have inputs to trigger them, a self triggering (also called refiring) mechanism is typically used to register events that trigger the source actor s next execution. 1. Discreteness here means the time stamps of all events are order isomorphic to a subset of natural numbers [22]. Events in a system are processed in chronological order. This implies that for any actor execution, the output events cannot be earlier in time than the input events that trigger them. This property, called causality, has profound semantics implications on discrete event systems [22] Because ....

....numbers [22] Events in a system are processed in chronological order. This implies that for any actor execution, the output events cannot be earlier in time than the input events that trigger them. This property, called causality, has profound semantics implications on discrete event systems [22]. Because of the continuous and global notion of time, and the discrete notion of events, discrete event models are usually used to model systems with discrete actions and timing concerns, like communication networks, digital circuits, and queueing systems. Many domain specific modeling tools and ....

E.A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Annals of Software Engineering, Special Volume on Real-Time Software Engineering, Vol. 7, 1999, pp. 25-45.

....is independent on the choice of ODE solvers. 16.8.S Mixed Signal Execution DE inside CT. Since time advances monotonically in CT and events are generated chronologically, the DE component receives input events monotonically in time. In addition, a composition of causal DE components is causal [51], so the time stamps of the output events from a DE component are always greater than or equal to the global time. From the view point of the CT system, the events produced by a DE component are predictable breakpoints. Note that in the CT model, finding the numerical solution of the ODE at a ....

E. A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Invited paper to Annals of Software Engineering, Special Volume on Real-Time Software Engineering, Volume 7, 1999.

....define an initialization, iteration, and termination phase, and within the iteration phase, it must define the same three phases of execution. The three phase iteration has proven suitable for a huge variety of models of computation, including synchronous dataflow (SDF) 58] discrete events (DE) [56], discrete time (DT) 28] finite state machines (FSM) 30] continuous time (CT) 66] synchronous reactive (SR) and Giotto (a time triggered domain) 39] All of these domains can be combined hierarchically. Some domains in Ptolemy II have fixed point semantics, meaning that in each iteration, ....

E. A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Annals of Software Engineering, Special Volume on Real-Time Software Engineering, vol. 7 (1999), pp. 25-45.

....CT Figure 4 shows a DE component wrapped by an event generator and a waveform generator. Since time advances monotonically in CT and events are generated chronologically, the DE component receives input events monotonically in time. In addition, a composition of causal DE components is causal [11], so the time stamps of the output events from a DE component are always greater than or equal to the global time. From the view point of the CT system, the events (i.e. breakpoints) produced by a DE component are predictable. Note that in the CT model, finding the numerical solution of the ODE ....

E.A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Annals of Software Engineering, Special Volume on Real-Time Software Engineering, vol. 7 (1999), p.25-45.

....or the traditional Rate Monotonic Scheduling (RMS) 20] Thus for synthesis, common modeling at this low level of abstraction has no advantages. Approaches to common modeling of substantially di erent semantics at a higher level of abstraction as needed for system synthesis are rare. The charts [21] model combines nite state machines (FSM) and a variety of concurrency models (e.g. SDF) in an alternating hierarchy. Thus, FSM states can be re ned by concurrency models and concurrency model nodes (e.g. data ow actors) can be re ned by FSMs. Restrictions most notably concerning termination ....

E.A. Lee, \Modeling concurrent real-time processes using discrete events," Annals of Software Engineering, 1998.

....CT Figure 4 shows a DE component wrapped by an event generator and a waveform generator. Since time advances monotonically in CT and events are generated chronologically, the DE component receives input events monotonically in time. In addition, a composition of causal DE components is causal [11], so the time stamps of the output events from a DE component are always greater than or equal to the global time. From the view point of the CT system, the events (i.e. breakpoints) produced by a DE component are predictable. Note that in the CT model, finding the numerical solution of the ODE ....

E.A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Annals of Software Engineering, Special Volume on Real-Time Software Engineering, vol. 7 (1999), p.25-45.

....an initialization, iteration, and termination phase, and it within the iteration phase, it must define the same three phases of execution. The three phase iteration has proven suitable for a huge variety of models of computation, including synchronous dataflow (SDF) 56] discrete events (DE) [54], discrete time (DT) 27] finite state machines (FSM) 29] continuous time (CT) 64] and Giotto (a time triggered domain) 38] All of these domains can be combined hierarchically. Some domains in Ptolemy II have fixed point semantics, meaning that in each iteration, the domain may repeatedly ....

E. A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Annals of Software Engineering , Special Volume on Real-Time Software Engineering, vol. 7 (1999), pp. 25-45.

....time, and the time maintained within a component the local time. DE inside CT Since time advances monotonically in CT and events are generated chronologically, the DE component will receive input events monotonically in time. In addition, a composition of causal DE components is causal [11], so the time stamps of output events from a DE component are always greater than or equal to those of the corresponding input events. Thus, from the CT system point of view, the events (breakpoints) produced by a DE component are always predictable. CT inside DE When a CT component is ....

....time interval) as well as a theoretical guide on the implementation of simulators. The mathematical framework I want to use is the tagged signal model developed by Lee and Sangiovanni Vincentelli [12] The model has been shown to be effective in studying the denotational semantics of DE models [11]. The first question I am trying to answer is related to determinism. Although both DE models and CT models can individually be shown to have a unique behavior under simple conditions (using Cantor metric and space, respectively) the conditions for mixed signal model may not be trivial. A reason ....

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E.A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Invited paper to Annals of Software Engineering, Special Volume on Real-Time Software Engineering, to appear.

....communication like round robin scheduling or the traditional Rate Monotonic Scheduling (RMS) 13] Thus for synthesis, common modeling at this high level of detail has no advantages. Approaches to common modeling of substantially different semantics for synthesis are rare. Lees recent work [11] defines a common description, which not only captures the system behavior in a uniform fashion but uses the same level of detail as in the (abstract) input description. Thus, even common simulation or verification become possible at a high level of abstraction. The resulting model, however, is ....

....possible at a high level of abstraction. The resulting model, however, is comprehensive and does not consider behavioral intervals. In our previous work, we found that behavioral intervals are a key property to efficiently capture incompletely known or heavily data dependent behavior. Therefore, [11] appears less suitable for synthesis, while the SPI model is of limited expressiveness for system verification. Other approaches can be found which extend the existing models or provide rules for the transition between different models, as for instance the PCC model proposed in [8] The PCC ....

E.A. Lee. Modeling concurrent real-time processes using discrete events. Annals of Software Engineering, 1998.

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E. A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Invited paper to Annals of Software Engineering, Special Volume on Real-Time Software Engineering, Volume 7, 1999.

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E. A. Lee, "Modeling Concurrent Real-time Processes Using Discrete Events," Invited paper to Annals of Software Engineering, Special Volume on Real-Time Software Engineering, to appear, 1998. Also UCB/ERL Memorandum M98/7, March 4th 1998.(http://ptolemy.eecs.berkeley.edu/ publications/papers/98/realtime)

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