20
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems.

          Related collections

          Most cited references40

          • Record: found
          • Abstract: not found
          • Article: not found

          Cassandra

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            New Generation Sensor Web Enablement

            Many sensor networks have been deployed to monitor Earth’s environment, and more will follow in the future. Environmental sensors have improved continuously by becoming smaller, cheaper, and more intelligent. Due to the large number of sensor manufacturers and differing accompanying protocols, integrating diverse sensors into observation systems is not straightforward. A coherent infrastructure is needed to treat sensors in an interoperable, platform-independent and uniform way. The concept of the Sensor Web reflects such a kind of infrastructure for sharing, finding, and accessing sensors and their data across different applications. It hides the heterogeneous sensor hardware and communication protocols from the applications built on top of it. The Sensor Web Enablement initiative of the Open Geospatial Consortium standardizes web service interfaces and data encodings which can be used as building blocks for a Sensor Web. This article illustrates and analyzes the recent developments of the new generation of the Sensor Web Enablement specification framework. Further, we relate the Sensor Web to other emerging concepts such as the Web of Things and point out challenges and resulting future work topics for research on Sensor Web Enablement.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Web technologies for environmental Big Data

                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                29 October 2016
                November 2016
                : 16
                : 11
                : 1813
                Affiliations
                [1 ]State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China; zlj0808@ 123456whu.edu.cn (L.Z.); 2015206190004@ 123456whu.edu.cn (S.Y.); czq0119@ 123456whu.edu.cn (Z.C.)
                [2 ]Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China
                Author notes
                [* ]Correspondence: cnc@ 123456whu.edu.cn ; Tel.: +86-27-6877-9996
                [†]

                These authors contributed equally to this work.

                Article
                sensors-16-01813
                10.3390/s16111813
                5134472
                27801869
                a0f554c6-0d7b-4ba3-9f80-f34eb937940d
                © 2016 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 August 2016
                : 24 October 2016
                Categories
                Article

                Biomedical engineering
                cloud computing,data retrieval,beidou positioning sensor,spatial-temporal data

                Comments

                Comment on this article