## 4 Conceptual Architecture  
Data visualisation and reporting are considered vital for useful results analysis [64; 65]. In real-time computing, feasibility analysis and formal proof of the input tasks require more attention since real-time systems, if properly not analysed, could lead to a deadline failure [18; 34]. Effective visualisation techniques help greatly analysing such system and can reduce the effort of the analysis with visual effects. Many tools are proposed in different researches to realise the visualisation and simulation of tasks as discussed in introductory sections. Some of the shortcomings of those tools are platform dependency and not keeping up with newer technology trends [47]. Moreover, the majority of them are desktop-based and is not compliant with cloud technologies. The need to have a generic tool which utilises start-of-the-art latest technologies and platform independence to some extent arises lately. The use of cloud technologies is widespread in the IoT context. This paper proposes a cloud-centric web-based tool to enable simulation, visualisation and tracking IoT tasks more adequately. The use of a cloud-centric web-based tool offers several benefits over traditional desktop technologies. First and foremost, the web-based tool can be accessed remotely, so the application user does not necessarily go on premises to use the tool and analyses the tasks. Second, due to the modern visualisation technologies in the web like HTML5 canvas, web containers, javascript, HTML5 and CSS3 the job is getting more comfortable but at the same time more effective. Finally, the open-source maintainers of these technologies are very active and continuously provide patches to reflect on the latest trends. The idea of this paper is to have a visualisation and simulation toolkit based on web technologies which can act as a valuable tool for understanding and undertaking the input tasks and feasibility of them. The initial sitemap of the tool is exhibited in Figure 3. There are three main modules of the tool; Input, Output and Process. Input module deals in tasks generation. A task can be added, edited, uploaded in batches and can be deleted. As discussed in previous sections, tasks can be of periodic nature or event-driven nature. Nonetheless, all tasks have some common attributes like arrival time, deadline, periods, urgency, and slack. Process deals in applying schedulingalgorithms to input process. As a proof of concept, two existing algorithms are considered: EDF and RM. EDF is used for event-based tasks while RM is used for periodic tasks. Lastly, output deals in presenting algorithms' result in effective user experience (UX) interface and leverage the power of HTML5/CSS3 for visualisation of the CPU analysis. It has different interfaces for presenting different scheduling algorithms, but the overall idea of representing scheduling algorithms' outcome in a better UX way is the central focus of all the interfaces. The parameters of input tasks are summarised in Table 2. Table 3, in the same way, identifies and describes the parameters utilised in the process. Finally, Table 4 shows the output performance measures of a specific algorithm. \begin{table}
\begin{tabular}{p{142.3 pt} p{284.5 pt}} \hline \hline
**Parameters** & **Definition** \\ \hline Start time or arrival time & The arrival of tasks also called phase of the tasks. \\ Execution time & The time it requires to execute during its period, in other words, The execution time within its period. \\ Period & The time after which the tasks repeat itself. This parameter is specific to periodic tasks only, and for sporadic tasks it is irrelevant. \\ Urgency & Urgency is the quantitative measure of the priority of the tasks. 0 means less urgent, one means highly urgent. It is only for event-driven tasks and irrelevant for periodic tasks. \\ Deadline & The maximum time limit in which the task must have to be executed otherwise will be considered invalid. For event tasks, the deadline is considered 0. \\ \hline \hline \end{tabular}
\end{table}