# A Methodology for the Design of Application-Specific Cyber-Physical Social Sensing Co-Simulators
## 1 Introduction
In any case, it must be noted that how the social world is integrated into CPS/IoT in order to create CPSS systems is an open issue [20]. Some works (the oldest ones) monitors social information by means of user surveys or user interfaces [24], defining kind of collaborative platforms (in order to forecast the bus arrivals [25] for example). Other define sensor networks were nodes interact with others and share information as people do in social networks [26]. Finally, and probably the most popular approach nowadays, some authors understand that CPSS should monitor people in a passive way (without human intervention, surveys or interfaces) as CPS monitors temperature or manufacturing process. In order to do that, sensors included in intelligent terminals are usually employed [27; 28]. Using the acquired information, people behavior, movement, etc. could be tracked and the environment (public infrastructure, such as airports, for example) would react to this social information. In this work, we are following the last approach, considering that CPSS are systems focused on monitoring people social behavior in a passive, unobtrusive and non-intrusive way. The most important difficulty that CPSS designers face is the problem of constructing large systems, including thousands of devices, people and a great amount of information [29]. Besides, CPSS have to manage very different abstraction levels, from the high-level information typical of the social world, to the very low-level information, so common in the cyber world (especially when hardware is considered) [20]. In order to address this problem, application-specific tools are necessary for specifying and validating designs and simulating systems. Nowadays, specific tools are employed to simulate each domain independently (a social simulator for the social world, a network simulator for the cyber world, etc.). This solution is very efficient in time, as each tool is extremely optimized to simulate a specific domain. In fact, most new tools for CPSS simulation would be less efficient and would require more computing power [30]. However, this situation also presents important disadvantages. Mainly, it firstly forces the decomposition of the CPSS scenario in different subsystems, simulating each domain in one environment and, later, relates the results obtained from each tool. All these actions must be performed by different experts, simulations becoming a very costly and complicated task. Thus, despite the probable inefficiency in time, the future is the co-simulation [31]. Nevertheless, today there is a lack of co-simulation instruments being able to simulate together all domains which made up a CPSS. The main cause of this situation is the difficulty of relating \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Concept** & **Physical World** & **Social World** & **Cyber World** \\ \hline Cyber-Physical systems & x & & x \\ Social Internet-of-Things & & x & x \\ Social Environment & x & x & \\ Social sensing & & x & x \\ CPSS & x & x & x \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Different concepts about the relations among the CPSS subsystems. correctly the simulation of various subsystems, as well as the complexity of interaction with final users in order to acquire the necessary co-simulator's requirements and characteristics. In particular, integrating and/or synchronizing various simulation tools implies modifying the execution routine or the communication and graphic interfaces among other tasks. Moreover, interacting with final users in order to acquire the required system characteristics implies to coordinate a communication process among all the stakeholders. Most of these activities are very time consuming and many times researches, companies or users do not implement new co-simulation tools for not being sure whether the effort is worthwhile.