Diffusion Utility Increment Based Crowdsensing Data Transmission Model over City Public Traffic System

摘要

The mobile smart devices are becoming more and more powerful, and they have been pervasively applied in crowdsensing as effective tools to solve large-scale sensing tasks in urban areas. However, some crowdsensing tasks may bring high network traffic costs to participants using 3G/4G network. In this paper, a novel data diffusing and transmission method is proposed in Crowdsensing based on city Public Traffic System (PTS). This method makes full use of the advantages that the bus has predictable trajectory, wide coverage area, fast moving speed and long contact duration among passengers, so as to realize the rapid transmission of large-scale sensed data. Firstly, we design a data diffusing and transmission model in PTS, and emphatically discuss the Multi-data diffusion and transmission in budget constraints. Secondly, we propose a new algorithm called BUI-BA (Backhaul Utility Increment Based Backhaul Algorithm), which is able to transmit multi- data at the same time. And the algorithm is explained in detail with an example. Finally, the performance of BUI-BA is evaluated with comparisons to Greedy and effSense from aspects like overall transmission utility, fairness, success rate of transmission and transmission redundancy. The result has proved that BUI-BA has a better overall performance and can achieve a tradeoff between overall transmission utility and transmission redundancy, and save more network traffic costs and some other resources for mobile nodes.