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Abstract: spatio-temporal databases aim at appropriately managing moving objects so as to support various types of queries. While much research has been conducted on developing query processing techniques, less effort has been made to address the issue of when and how to update location information of moving objects. Previous work shifts the workload of processing updates to each object which usually has limited CPU and battery capacities. This results in a tremendous processing overhead for each moving object. In this paper, we focus on designing efficient update strategies for two important types of moving objects, free-moving objects (FMOs) and network-constrained objects (NCOs), which are classified based on object movement models. For FMOs, we develop a novel update strategy, namely the FMO update strategy (FMOUS), to explicitly indicate a time point at which the object needs to update location information. As each object knows in advance when to update (meaning that it does not have to continuously check), the processing overhead can be greatly reduced. In addition, the FMO update procedure (FMOUP) is designed to efficiently process the updates issued from moving objects. Similarly, for NCOs, we propose the NCO update strategy (NCOUS) and the NCO update procedure (NCOUP) to inform each object when and how to update location information. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed update strategies.

具有变动速度之自由移动与移动受限物体位置更新策略设计

研究目的：为有效管理空间中具有变动速度之自由移动物体以及移动受限物体，设计更新策略，告知移动物体何时该更新自己的位置信息至服务器端，以显著降低移动物体计算成本。另外，设计更新程序以使服务器端有效率地处理物体更新。
方法提亮：针对自由移动与移动受限物体，明确地给出一个时间点。有此时间点，移动物体无需随时随地判断是否需要更新。对于服务器端，更新程序可以有效且快速地处理每个物体传回的更新需求。
重要结论：本文设计的更新策略可显著降低移动物体的处理成本。藉由本文设计的更新程序，可有效减少服务器端物体更新的处理成本，进而快速处理同时发生的物体更新。
时空数据库；移动物体；自由移动物体；移动受限物体

[1]Brinkhoff, T., 2002. A framework for generating network-based moving objects. GeoInformatica, 6(2):153-180.

[2]Chen, S., Ooi, B.C., Zhang, Z., 2010. An adaptive updating protocol for reducing moving object database workload. Int. Conf. on Very Large Data Bases, p.735-746.

[3]Cheng, R., Kalashnikov, D.V., Prabhakar, S., 2004. Querying imprecise data in moving object environments. IEEE Trans. Knowl. Data Eng., 16(9):1112-1127.

[4]Chung, B.S.E., Lee, W.C., Chen, A.L.P., 2009. Processing probabilistic spatio-temporal range queries over moving objects with uncertainty. Int. Conf. on Extending Database Technology, p.60-71.

[5]Forlizzi, L., Güting, R.H., Nardelli, E., et al., 2000. A data model and data structures for moving objects databases. Int. Conf. on ACM Management of Data, p.319-330.

[6]Güting, R.H., Bohlen, M.H., Erwig, M., et al., 2000. A foundation for representing and querying moving objects. ACM Trans. Database Syst., 25(1):1-42.

[7]Huang, Y.K., Lee, C., 2010. Efficient evaluation of continuous spatio-temporal queries on moving objects with uncertain velocity. GeoInformatica, 14(2):163-200.

[8]Huang, Y.K., Liao, S.J., Lee, C., 2009. Evaluating continuous K-nearest neighbor query on moving objects with uncertainty. Inform. Syst., 34(4-5):415-437.

[9]Huang, Y.K., Su, I.F., Lin, L.F., et al., 2013. Efficient processing of updates for moving objects with varying speed and direction. Int. Conf. on Advanced Information Networking and Applications, p.854-861.

[10]Sistla, A.P., Wolfson, O., Chamberlain, S., et al., 1997. Modeling and querying moving objects. Int. Conf. on Data Engineering, p.422-432.

[11]Song, Z., Roussopoulos, N., 2001. K-nearest neighbor search for moving query point. Int. Conf. on Spatial and Temporal Databases, p.79-96.

[12]Tao, Y., Papadias, D., 2002. Time parameterized queries in spatio-temporal databases. Int. Conf. on ACM Management of Data, p.334-345.

[13]Tao, Y., Faloutsos, C., Papadias, D., et al., 2004. Prediction and indexing of moving objects with unknown motion patterns. Int. Conf. on ACM Management of Data, p.611-622.

[14]Wolfson, O., Yin, H., 2003. Accuracy and resource consumption in tracking and location prediction. LNCS, 2750:325-343.

[15]Wolfson, O., Sistla, A.P., Chamberlain, S., et al., 1999. Updating and querying databases that track mobile units. Distr. Parall. Databases, 7(3):257-387.

[16]Xiong, X., Mokbel, M.F., Aref, W.G., 2005. SEA-CNN: scalable processing of continuous K-nearest neighbor queries in spatio-temporal databases. Int. Conf. on Data Engineering, p.643-654.

[17]Xiong, X., Mokbel, M.F., Aref, W.G., 2006. LUGrid: update-tolerant grid-based indexing for moving object. Int. Conf. on Mobile Data Management, p.13-20.

[18]Yu, X., Pu, K.Q., Koudas, N., 2005. Monitoring K-nearest neighbor queries over moving objects. Int. Conf. on Data Engineering, p.631-642.