移动目标数据库(moving object database)有别于一般数据库技术的重要特征之一就是不仅可以对移动目标在数据库记录的时刻进行位置查询,而且可以对不同记录时刻之间以及未来时刻的位置进行查询,其研究的首要问题是建立移动目标运动及位置更新模型.目前有大量依靠其他辅助设备(如GSM网络)定位的盲终端设备(如移动电话,PDA等),存在着MOD管理的潜在需求,需要对它们建立合适的运动及位置更新模型,来为移动用户提供基于位置的服务.针对这类无自定位能力的移动目标,利用它们通常运动在城市的道路网络上这一特点,提出了基于道路网络的移动目标历史和未来速度计算模型,在此基础上提出了基于道路网络的非等时位置更新模型.与传统的速度计算模型相比,基于道路网络的移动目标历史和未来速度计算模型在考虑移动目标定位误差时可以降低移动目标位置预测的误差;与等时位置更新模型相比,基于道路网络的非等时位置更新模型在平均预测误差相近的情况下,可以减少移动目标和定位设施之间的通信量.
An important feature that differentiates moving object database (MOD) from other databases is that MOD can support queries for locations recorded not only at the sample time, but also at time between samples and even at time in the future. The most important issue in MOD research is to build models of moving objects?mobility and their locations update. The advance in mobile Internet and location-based services requires appropriate models be built for popular dumb terminals, such as cell phones, which can only be located by auxiliary facilities like GSM/CDMA networks. Considering that users of such kind dumb devices often move on the road network, a novel model for these moving objects to calculate their velocities in the past and future and to update their locations with varied sample time based on road network is presented in this paper. Compared with traditional velocity models, the proposed model can reduce the location prediction errors effectively. And when comparing with the model of updating locations with uniform sample time, the proposed model can reduce the communication traffic between moving objects and locating facilities with the same average prediction error.