As the data size on smart things continue to grow, it becomes inefficient to transfer the massive raw data to centralized cloud datacenters for the analysis of raw data and the deployment of innovative and novel services into various areas such as smart cities, etc. As the concept of Fog Computing, the structure of distributed intelligent infrastructure can address those problems by providing elastic resources and services to end users with smart devices at the edge of network. Hence, through the functions of analytics and flexible control based on the Software‐Defined Network (SDN), it is necessary to provide the SDN‐driven management intelligence, which can maximize network utilization subject to constraints on service priority and resources fairness by differentiating service flows according to the quality requirements. This paper proposes the SDN controller for intelligent inter‐datacenter (inter‐DC) cloud networking, which enables optimal traffic loads distribution across the distributed datacenters with the global inter‐DC view of link states and flow statistics by applying the network‐aware flow scheduling on a policy‐driven inter‐DC traffic control layer. The proposed intelligent inter‐DC controller performs a global resources scheduling mechanism that uses different weights according to the priority of service class in allocating bandwidths based on multi‐layers networking interconnecting the distributed datacenters.

This study presents the design of a service‐oriented networking platform to offer dynamic networking services in support of mobile group communications among connected smart devices. This platform enables users to access smart services anywhere and anytime with embedded devices while satisfying their requirements of various smart services. The proposed platform adopts a session initiation protocol (SIP) protocol as service signalling protocol that provides high extensibility and compatibility with an existing service system. The overlay network structure suggested in our platform provides an advantage of building a scalable and dynamic service network based on multiple smart zones. Furthermore, the quality of end‐to‐end service in dynamic network environments is guaranteed by virtue of the smart delivery scheme in the platform.

Existing sensor network simulators are not appropriate for indoor sensor network systems. We present RealSSim, the sensor network simulator especially developed for indoor sensor networks. RealSSim considers the structure of buildings and the quality of construction materials for accurate radio propagation analysis. It also supports an attractive visualization of the level as commercial products. In our demonstration, we show the whole process of simulation for two indoor sensor network systems.