Abstract
The recent emerging trend to promote the harmonious interactions between human and smart objects in Internet of Things (IoT) applications has led to the rising demand for the comprehensive exploration of associated IoT design spaces, considering system-, network-, and human-level perspectives. The traditional design approach of networked smart objects tends to ignore the effects caused by human interactions so that the existing approach has the limited capability in joint system/network/human multi-level exploration. In this paper, we propose a high-level system modeling and multi-level simulation approach for microsystem models to interoperate with high-level models in the human-level perspective and to provide comprehensive co-exploration. The high-level system modeling enables one to abstract the detailed operations of hardware platforms using power and timing data obtained by the proposed high-level state-based profiling method and using the event-driven modeling concept. For the event-driven system modeling, we utilize the discrete-event system specification (DEVS) to support scalable model-driven prototyping. To represent the coupled relationship of network-level system activity and human-level interactions between node systems and humans, we employ a general-purpose network simulator to model the operation and communication of network modules in smart objects and developed agent-based human behavioral models. For the co-simulation of multi-level models, we designed a distributed simulation platform to enable the interoperation between the DEVS simulator and the network simulator using a runtime infrastructure. The proposed modeling and simulation approach is applied for the multi-level evaluation of a smart museum application to estimate the effect of energy-efficiency policies.
Highlights
In various Internet of Things (IoT) applications for humancentered services, smart objects are being designed to interact with humans by sensing individualized behaviors (Mafrur et al 2015; Shtykh and Jin 2011) to collect and analyze social data
For the high-level modeling of micro-controller unit (MCU) in the smart object, we propose a profiling method to acquire timing and power data, which will form the model parameters related to defined high-level states
The ext is called by the discrete-event system specification (DEVS) simulator when there are external input events and the int is called when no event occurred until the current state sojourn has elapsed
Summary
In various Internet of Things (IoT) applications for humancentered services, smart objects are being designed to interact with humans by sensing individualized behaviors (Mafrur et al 2015; Shtykh and Jin 2011) to collect and analyze social data. When high-resolution MCU models cooperate with human dynamic models, it leads to a huge computation overhead which causes a scalability problem, because a relatively large amount of virtual simulation time (≥ 1 h) is required to capture social behaviors. For the high-level modeling of MCU in the smart object, we propose a profiling method to acquire timing and power data, which will form the model parameters related to defined high-level states. For the multi-level co-simulation, we designed a distributed simulation platform for the interoperation between the DEVS simulator and the NS-3, using a runtime infrastructure (RTI) HLA (2010a, b, c) This rest of the paper is organized as follows.
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