The increasing interest in the Internet-of-Things (IoT) suggests that a new source of big data is imminent---the machines and sensors in the IoT ecosystem. The fundamental characteristic of the data produced by these sources is that they are inherently geospatial in nature. In addition, they exhibit unprecedented and unpredictable skews. Thus, big data systems designed for IoT applications must be able to efficiently ingest, index and query spatial data having heavy and unpredictable skews. Spatial indexing is well explored area of research in literature, but little attention has been given to the topic of efficient distributed spatial indexing.
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