The Internet of Things (IoT) is now infiltrating into our daily lives, providing important measurement and collection tools to inform us of every decision. Millions of sensors and devices continue to generate data and exchange important information through complex networks that support machine-to-machine communication and monitor and control critical smart world infrastructure. As a strategy to alleviate resource congestion escalation, edge computing has become a new paradigm for addressing the needs of the Internet of Things and localization computing. Compared to well-known cloud computing, edge computing migrates data calculations or storage to the edge of the network near the end-user. Thus, multiple compute nodes distributed across the network can offload computational pressure from a centralized data center and can significantly reduce latency in message exchanges. Besides, the distributed architecture balances network traffic and avoids spikes in traffic in the IoT network, reduces latency between edge/cloud servers and end-users, and reduces response time for real-time IoT applications compared to traditional cloud services. In this article, we conducted a comprehensive survey to analyze how edge computing can improve the performance of IoT networks. We classify edge calculations into different groups based on the architecture and study their performance by comparing network latency, bandwidth usage, power consumption, and overhead. Through the systematic introduction of the concept of edge computing, typical application scenarios, research status, and key technologies, it is considered that the development of edge computing is still in the initial stage. There are still many problems in practical applications that need to be solved, including optimizing edge computing performance, security, interoperability, and intelligent edge operations management services.
High-voltage circuit breakers are important protection and control equipment in power systems. In order to understand the mechanical characteristics of vacuum circuit breaker, the mathematical relationship between the released energy of closing spring, the stored energy of opening spring and overtravel spring and the rotation angle of output crank arm is studied. The characteristic curve between the released energy of closing spring and the rotation angle of output crank arm and the characteristic curve between the stored energy of opening spring and overtravel spring and the rotation angle of output crank arm are drawn by MATLAB. In order to improve the matching of energy release and energy storage characteristic curves, a method of improving cam profile is proposed. The dynamics simulation model of spring operating mechanism of high voltage circuit breaker is established and the original cam and adjusted cam are imported into the dynamics simulation model of mechanism. The simulation results show that the adjusted cam improves the closing speed of vacuum circuit breaker. This helps to reduce the stress on the parts of the vacuum circuit breaker and increase the service life of the vacuum circuit breaker.
An approximate spherical circle-point of the moving rigid body in spherical motion is defined, and the approach of adaptive cone fitting is presented with respect to spherical curves. Then, the optimum synthesis of spherical four-bar linkages can be converted into an adaptive curve fitting. Thus, the mathematical model of saddle-point programming for this problem is established with the corresponding optimum algorithms proposed. Theoretically, it is provided that the existence of the best solution and the convergence of the optimum algorithms to optimum synthesis of spherical four-bar linkages. Finally, two numerical examples are given to show the feasibility and the validity for the approach.The 3rd Intetnational Conference on Innovative Computing Information and Control (ICICIC'08) 978-0-7695-3161-8/08 $25.00
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