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Under the existing loosely distributed sensor environment with heterogeneous data sources, transportation planning and management agencies have found a critical need for the efficient storage, processing, and extraction of network-level information. The emerging practice of cloud computing provides a revolutionary solution for network-level information needs. This paper introduces MapReduce, a distributed computing framework for the design of data-intensive software systems that can manage and manipulate a large volume of data. With a focus on a traffic-oriented, data-intensive application, the researchers designed and implemented a system for the provision of traveler information based on travel time reliability. The system leverages the unified data storage and computing platform provided by the cloud computing architecture.
Lei et al. (Sun,) studied this question.
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