Abstract
The development of Internet of Things (IoT) systems becomes difficult and time consuming. IoT simulation is desirable to provide a way to evaluate the system to save time and money. Current simulation tools only focus on the functional correctness but lack of execution information for design optimization. Particularly, it needs to identify the functions/objects in the original program that contain the executed instructions, which is essential in identifying bottlenecks. However, addition of the profiling ability slows down the simulation speed, it needs to support multiple simulation granularity at the functions/objects level to trade off simulation fidelity with simulation time. Furthermore, those tools also lack of supports for interactions with the environment. It needs to add environmental models in terms of time and location to dynamically inject environmental data to the simulated IoT devices. In this thesis, we present a multi-granular environment-modeling simulation platform for IoT end devices. We propose a source level profiling mechanism to allow generation of trace of executed instructions and link each executed instruction to the source level function. Our work is configurable to allow change of simulation granularity at the function level dynamically and support environmental modeling with external inputs to influence IoT simulation for the IoT end devices.