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With advanced ICT, the ever-rapid development of informatization has become an integral part of smart city services in healthcare, transportation, energy, education, business, community life, and so on. A huge amount of data, called big data, is generated from various sources, and effective analysis and utilization of big data has become a key factor in the success of smart city services. However, in order to achieve precise big data analytics and make real-time decisions, one of the challenging issues is how to efficiently deliver the huge amounts of collected data to the processing servers. In this article, we first propose a novel architecture to support smart city services based on SDN technology. Then we study the time-constrained big data transfer scheduling (TBTS) problem under the proposed architecture, and present an intelligent strategy to address the TBTS issue by utilizing the SDN controller to conduct dynamic flow control and multi-path transfer scheduling. Simulation results demonstrate that the proposed strategy can efficiently support big data transfer in terms of low transfer delay and high bandwidth utilization. [ABSTRACT FROM PUBLISHER]

The emerging real-time and computation-intensive services driven by the Internet of Things, augmented reality, automatic driving, and so on, have tight quality of service and quality of experience requirements, which can hardly be supported by conventional cloud computing. Fog computing, which migrates the features of cloud computing to the network edge, guarantees low latency for location-aware services. However, due to the locality feature of fog computing, maintaining service continuity when mobile users travel across different access networks has become a challenging issue. In this article, we propose a novel software-defined-networking-based fog computing architecture by decoupling mobility control and data forwarding. Under the proposed architecture, we design efficient signaling operations to provide seamless and transparent mobility support to mobile users, and present an efficient route optimization algorithm by considering the performance gain in data communications and system overhead in mobile fog computing. Numerical results from extensive simulations have demonstrated that the proposed scheme can not only guarantee service continuity, but also greatly improve handover performance and achieve high data communication efficiency in mobile fog computing. [ABSTRACT FROM PUBLISHER]