A Programming Model for Spatio-temporal Data Streaming Applications

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• 作者：Shigeru Imai ; ^{imais@cs.rpi.edu} ; Carlos A. Varela ^{cvarela@cs.rpi.edu}
• 关键词：programming models ; spatio-temporal data ; data streaming
• 刊名：Procedia Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：9
• 期：Complete
• 页码：1139-1148
• 全文大小：426 K

文摘

In this paper, we describe a programming model to enable reasoning about spatio-temporal data streams. A spatio-temporal data stream is one where each datum is related to a point in space and time. For example, sensors in a plane record airspeeds (va) during a given ?ight. Similarly, GPS units record an airplane's ?ight path over the ground including ground speeds (vg) at different locations. An aircraft's airspeed and ground speed are related by the following mathematical formula:, where v_a and ¦Á_a are the aircraft airspeed and heading, and v_w and ¦Á_w are the wind speed and direction. Wind speeds and directions are typically forecast in 3,000-foot height intervals over discretely located ?x points in 6-12 hour ranges. Modeling the relationship between these spatio-temporal data streams allows us to estimate with high probability the likelihood of sensor failures and consequent erroneous data. Tragic airplane accidents (such as Air France's Flight 447 on June 1st, 2009 killing all 216 passengers and 12 aircrew aboard) could have been avoided by giving pilots better information which can be derived from inferring stochastic knowledge about spatio-temporal data streams. This work is a ?rst step in this direction.