Mobile crowdsensing as a service: A platform for applications on top of sensing Clouds

• Emulation of deployment comparing (i) prototype of MCSaaS and (ii) current practices.
• Modeling of MCSaaS paradigm by Petri nets and evaluation against conventional MCS.
• Description of architectural elements of the platform and their interactions.
• MCSaaS platform for mass deployment of MCS apps, and their elastic user base adaptation.
• Mobile crowdsensing as a service paradigm for MCS apps design and deployment.

Consumer-centric mobile devices, such as smartphones, are an emerging category of devices at the edge of the Internet. Leveraging volunteers and their mobiles as a (sensing) data collection outlet is known as Mobile Crowd Sensing (MCS) and poses interesting challenges, with particular regard to the management of sensing resource contributors, dealing with their subscription, random and unpredictable join and leave, and node churn.To facilitate and expedite the (commercial) exploitation of this trend, in this paper we propose to adopt a service-oriented approach to cope with MCS application deployment into a sensing Cloud infrastructure, decoupling the MCS application domain from the infrastructure one. To this purpose we provide the building blocks for implementing such a novel take on MCS, which from a Cloud layering perspective can be identified as a platform service, i.e., an MCS as a service (MCSaaS). A prototype implementation that serves as a blueprint and a proof-of-concept of the proposed framework is presented, while an evaluation of the effectiveness of the MCSaaS paradigm has been provided using suitable mobility-related use cases for a validation of the concept, as well as a modeling approach through the adoption of generalized stochastic Petri nets.