Abstract
Discrete event system specification (DEVS) has been widely used in event-driven simulations for sensor-driven Internet of things (IoT) applications, such as monitoring the spread of fire disaster. Event-driven models for IoT sensor nodes and their communication is described in DEVS and they have to be integrated with continuous models of fire-spreading dynamics so that the hybrid system modeling and simulation approach have to be considered for both continuous behavior of fire-spreading and event-driven communications by large-scale IoT sensor devices. The hybrid-integrated modelling and simulation for fire-spreading in wide area and large-scale IoT devices result in more complex model evaluation, including simulation time synchronization, so that simulation acceleration is important by considering scalability in large-scale IoT-driven applications that sense fire-spreading. In this study, we proposed a scalable simulation acceleration of a DEVS-based hybrid system using heterogeneous architecture based on multi-cores and graphic processing units (GPUs). We evaluated the power consumption comparison of the proposed accelerated-simulation approach in terms of the composition of the event-driven IoT models and continuous fire-spreading models, which are tightly described in differential equations across a large number of cellular models. The demonstrated result shows that the full utilization of CPU-GPU integrated computing resources, on which event-driven models and continuous models are efficiently deployed and optimally distributed, could enable an advantage for high-performance simulation speedup in terms of execution time, although more power consumption is required, but the total energy consumption could be reduced due to fast simulation time.
Highlights
Simulation has been widely used to solve various problems in dynamic systems where the characteristics of a system are not statically described in analytic equations. discrete event system specification (DEVS)-based modeling and simulation (M&S) [1] has been widely adopted as an efficient simulation framework by splitting the model description part and simulation-related tasks
DEVS is used for modular, layered formalism, including a discrete event system based on state transition, a continuous state system represented by differential equations, and a hybrid system in which both exist
We implemented an accelerated simulation of a DEVS-based hybrid system using a heterogeneous architecture, such as tight coupling of multi-cores and graphic processing units (GPUs)
Summary
Simulation has been widely used to solve various problems in dynamic systems where the characteristics of a system are not statically described in analytic equations. discrete event system specification (DEVS)-based modeling and simulation (M&S) [1] has been widely adopted as an efficient simulation framework by splitting the model description part and simulation-related tasks. DEVS-based M&S has been applied and studied [2,3,4] to accelerate the simulation speed with a reasonable fidelity for a hybrid system with complex behaviors, which are simultaneously described in a discrete event model and continuous time model. The hybrid system has continuous and discrete dynamic behavior, and it is characterized by interactions between the continuous system and the discrete event system. DEVS is used for modular, layered formalism, including a discrete event system based on state transition, a continuous state system represented by differential equations, and a hybrid system in which both exist. A real system modeled using DEVS can be depicted as a set of atomic and coupled models
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