Research On The Optimal Control Algorithms Of Data Gathering Devices And Processing Platform For Crowd Sensing

In recent years, with the in-depth development of the Internet of things(IOT), Crowd Sensing(CS) as a low-cost and more flexible model of IOT has been widely concerned. Currently, the research on CS perception is mostly based on special application and demand, and the application platform is constructed without considering the randomness of the request, the availability of resources, the incentive mechanism for the participation of users and so on. It is very important for the research and development of CS to find a more common platform for the optimal scheduling of data collection and resource allocation.In this paper, we focus on the optimization control of the data gathering devices and processing platform based on CS mode. Under the condition of random network environment, the request of dynamic arrival and the availability of computing resources, achieve the time-average utility optimization of mobile devices and the time-average profit maximization by using Lyapunov optimization theory. The main work and contributions of this thesis are as follows:First, based on the Lyapunov optimization for CS model, to solve the optimization problem of sensing part and platform section. Lyapunov optimization theory is mainly focus on communication and queueing systems. In stochastic network environment, under the condition of time average constraints, such as networks with random events, time variation and uncertainty, ensure the stability of the system and make the online control decisions to solve the optimization problem of a time average (or a function of time averages). Compared with the traditional techniques such as dynamic programming and Markov decision process, Lyapunov optimization algorithm does not need long-term historical statistics, not for a particular scene, there is a better mobility and computational complexity.Second, Construct the optimal control model of the mobile device in CS, ensure the best use of energy in data transmission, and maximize the time-average utility of the device. This paper analyzes the process of data collection and transmission of mobile devices and modeling, using the Lyapunov optimization theory, design the optimization control algorithm. Through theoretical analysis and simulation experiments, it is proved that the proposed algorithm can ensure the stability of the system and achieve the optimal utility of mobile devices.Third, Construct the optimal control model of the processing platform in CS, achieve the trade off between the system throughput and cost, and maximize the time-average profit of the system. In this paper, the system composed of mobile users, cloudlets and processing platform, based on the Lyapunov optimization theory and the technique of weight perturbation, we design a new stochastic control algorithm.Through theoretical analysis and simulation experiments, it is proved that the proposed algorithm can ensure the steady state of the system and achieve the maximum profit of the platform.