Mining the Traffic Cloud: Data Analysis and Optimization Strategies for Cloud-Based Cooperative Mobility Management
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.
KeywordsCloud computing architecture ambient intelligence distributed data processing and mining multi-agent systems distributed decision-making
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