A Distributed Proactive Service Framework for Crowd-Sensing Process

ith the wide deployment of various kinds of sensors in fixed infrastructures and in mobile devices, technologies and applications of crowd-sensing has drawn attentions in the fields of mobile computing. This paper studies the design of frameworks for crowd-sensing process in a distributed environment. We discuss the realization of the compatibilities of devices and services, as well as the algorithms of dealing with transmitting and accessing large amount of sensing data. We present a new distributed crowd-sensing framework called DASF, which is based on context data servers. The framework consists of three layers: hardware device layer, context data layer, and smart service layer. The key innovations and features of the framework are illustrated in detail. Through experiments and results analyses, DASF is shown to have good compatibility in heterogeneous device platforms, and it is capable of dealing with heavy load of accessing with practical significance.