The Internet of Things (IoT) consists of resource-constrained smart devices capable to sense and process data. It connects a huge number of smart sensing devices, i.e., things, and heterogeneous networks. The IoT is incorporated into different applications, such as smart health, smart home, smart grid, etc. The concept of smart healthcare has emerged in different countries, where pilot projects of healthcare facilities are analyzed. In IoT-enabled healthcare systems, the security of IoT devices and associated data is very important, whereas Edge computing is a promising architecture that solves their computational and processing problems. Edge computing is economical and has the potential to provide low latency data services by improving the communication and computation speed of IoT devices in a healthcare system. In Edge-based IoT-enabled healthcare systems, load balancing, network optimization, and efficient resource utilization are accurately performed using artificial intelligence (AI), i.e., intelligent software-defined network (SDN) controller. SDN-based Edge computing is helpful in the efficient utilization of limited resources of IoT devices. However, these low powered devices and associated data (private sensitive data of patients) are prone to various security threats. Therefore, in this paper, we design a secure framework for SDN-based Edge computing in IoT-enabled healthcare system. In the proposed framework, the IoT devices are authenticated by the Edge servers using a lightweight authentication scheme. After authentication, these devices collect data from the patients and send them to the Edge servers for storage, processing, and analyses. The Edge servers are connected with an SDN controller, which performs load balancing, network optimization, and efficient resource utilization in the healthcare system. The proposed framework is evaluated using computer-based simulations. The results demonstrate that the proposed framework provides better solutions for IoT-enabled healthcare systems.

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Based on the rough set theory, a new distribution network fault diagnosis approach to deal with the imperfect alarm signals that caused by malfunction or failing operation of protection relays and circuit breakers, error in the communication equipment is proposed. Due to rough set theory can effectively handle the imprecise problems without any ancestor information except the data set itself, a decision table including all kinds of fault cases is established by considering the signals of protection relays and circuit breakers, and the approach can extract diagnosis rules from the set of fault samples directly. The inherent redundancy in the alarm information is exposed. Finally, a practical fault diagnosis program of the typical distribution network is proposed by using Visual C# language based on Visual Studio.NET developing platform. The result shows the validity of the proposed method.

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One of the key features of cloud computing is on demand resource provision. Unfortunately, different cloud service providers often have different standards, which makes the job of choosing the suitable resource to be a very difficult one for the common users. Then the technology of service broker came out which is designed to choose the appropriate services among different providers to meet the user's requests. Besides get the final computing results, there are many other conditions often be taken into account, like energy consumption and response time. Maximizing the energy efficiency is not only good for the environment protection but also could benefit the user and provider financially. This paper proposed an energy-aware service brokering strategy, which aimed at finding a suitable tradeoff between energy consumption and user satisfaction. The simulation results have shown that the proposed strategy can effectively reduce the level of energy consumption and meanwhile maintain the user satisfaction at a reasonably good level.