## 2 Related Work
### Overview of Real-Time Systems Scheduling and Visualisation Tools  
The main research problem addressed in this paper is to investigate the existing tools for the simulation of real-time systems and formally prove the deadline of these systems in IoT applications. To cope with this, the efforts in real-time systems to propose such tools are discussed. Real-time systems are one of the oldest research areas, and in its early development stage, numerous simulators were designed for general purpose real-time systems. In the early 1990s, some notable advancement has been made. For instance, a tool named STRESS [37] was proposed by [PERSON] et al. which considered the first notable tool of it's time for real-time task simulations. It was written in a new programming language called STRESS and had the flexibility of adding new algorithms for simulation without modifying the core. Another effort came in the form GHOST by [PERSON] et al. [38], which supported diverse types of tasks in contrast to the previous efforts which only supported a single category of tasks, e.g., periodic tasks. In [39] an attempt was made to design a simulation tool for hybrid task sets on distributed systems with the support of shared resources and also had a native visualisation in its core. However, the maintenance state of this project is unknown, and the source code is not open-source. In the post 2000 era, simulation tools like MAST [40], VizzSchedular [41], ARTISST [42], STORM [43], Realtss [44], Cheddar [45] and Simso [46] have been proposed. Their end goal was to support simulation and feasibility analysis of more recent scheduling policies. They used relatively newer technologies offering better user experience interfaces. However, these tools also face the same problem of keeping up with the latest trends, and the maintenance state of many of them are unknown. Additionally, the visualisation techniques implemented in these tools are based on desktop technologies and do not consider a more dynamic IoT context in which the tasks are remotely configured and scheduled without the need to go on premises. Finally, these tools are purely aimed at simulation and visualisation of tasks and do not focus on monitoring of input tasks in real-time IoT scenario [43; 45]. The majority of these tools are no longer maintained, and their source code is not open. In the recent past, there have been several efforts focused towards building simulation tools which can effectively simulate and visualise the behaviour of real-time systems in the context of IoT. A recent study has been conducted by [PERSON] et al. on these real-time task scheduling tools to highlight the shortcoming of the traditional tools when utilised in the context of IoT, and the need to have a tool which focuses on latest web-based technologies rather than conventional, outdated technologies are encouraged [47]. The difference between the traditional simulation tools and the modern IoT-based real-time simulation tools is not subtle. Most of the constraints like deadline, energy and power hold same for IoT application as well. However, in the latter case, the real-time operations and jobs should be performed on a much larger scale, and thus the applications need to degrade gracefully by employing proper load-balancing techniques [48]. Nevertheless, with the application of real-time systems in IoT and industry 4.0, there is still a dire need of a testbed to simulate the footprint of the system to understand the behaviour to a full extent. One of such efforts is put by [PERSON] et al. which is named as SDMSim [49] to realise and understand the intelligent supply-demand modelling in smart factories. The tool supports the formulation of supply-demand, statistical analysis and visualisation; however, it is not generic in purpose and very specific to the scenario for which it is proposed. ScSF [50] by [PERSON] et al. is another similar effort based on high performance computing (HPC) systems. This tool presents an environment to simulate workloads and tasks for large-scale tests.