Mining the Traffic Cloud: Data Analysis and Optimization Strategies for Cloud-Based Cooperative Mobility Management

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 220)


Future Internet (FI) technologies can considerably enhance the effectiveness and user friendliness of present cooperative mobility management systems (CMMS), providing considerable economical and social impact. Real-world application scenarios are needed to derive requirements for software architecture and smart functionalities of future-generation CMMS in the context of the Internet of Things (IoT) and cloud technologies. The deployment of IoT technologies can provide future CMMS with huge volumes of real-time data that need to be aggregated, communicated, analysed, and interpreted. In this study, we contend that future service- and cloud-based CMMS can largely benefit from sophisticated data processing capabilities. Therefore, new distributed data mining and optimization techniques need to be developed and applied to support decision-making capabilities of future CMMS. This study presents real-world scenarios of future CMMS applications, and demonstrates the need for next-generation data analysis and optimization strategies based on FI capabilities.


Cloud computing architecture ambient intelligence distributed data processing and mining multi-agent systems distributed decision-making 


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Institute of InformaticsClausthal University of TechnologyClausthal-ZellerfeldGermany

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