Assessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities

The Internet of Things (IoT) paradigm makes the Internet more pervasive. IoT devices are objects equipped with computing, storage and sensing capabilities and they are interconnected with communication technologies. Smart cities exploit the most advanced information technologies to improve public services. For being effective, smart cities require a massive amount of data, typically gathered from sensors. The application of the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms and to produce a large amount of data following Sensing as a Service (S(2)aaS) business models. Having citizens involved in the process through mobile crowd-sensing (MCS) techniques unleashes potential benefits as MCS augments the capabilities of existing sensing platforms. To this date, it remains an open challenge to quantify the costs the users sustain to contribute data with IoT devices such as the energy from the batteries and the amount of data generated at city-level. In this paper, we analyze existing solutions, we provide guidelines to design a large-scale urban level simulator and we present preliminary results from a prototype.