基于公交网络的车载群智感知方法及其优化

Strategy and optimization for public bus network-based vehicular crowd sensing

公交车具有固定的行驶路线和发车周期、统一的车载设备标准、低隐私泄露风险等特性。根据公交车的特性,设计了一个基于公交网络的车载群智感知系统,系统中的数据中心通过公交网络中的公交车来采集城市数据,以满足数据用户的需求;随后研究系统中的任务分配问题和数据交易问题。基于贪婪算法设计优化任务分配策略以最小化系统的数据采集能耗成本,并根据博弈论设计最优数据交易策略以最大化系统的经济效益。最后通过仿真,验证了提出的策略的有效性和优越性。

Public buses have unique characteristics,such as fixed moving paths and time periods,uniform vehicular device standards,low risk of privacy exposure.This paper designed a public bus network-based vehicular crowd sensing system,considering the characteristics of public buses.In the system,data center utilized public buses of the bus network to collect urban data which was required by data users.It also studied the task assignment problem and the data trading problem in the system.This paper proposed an optimized task assignment strategy based on a greedy algorithm to minimize the system energy consumption of data collection,and proposed an optimal data trading strategy based on game theory to maximize the system utility.Finally,numerical results demonstrate the effectiveness of proposed strategies.