Abstract
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.
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