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With the progress of highway construction technology and the difficulty of operation, cross-operation becomes emerging constantly, but safety accidents also appear constantly and the problem is how to ensure the cross-operation security. In order to ensure the safety of highways cross operation, we evaluated the security of cross-operation. We choose the method of fuzzy AHP which can quantify the qualitative data. In the selection of indicators, we choose “exchange of information” as an index which evaluated the security of cross-operation of YIBA highway construction by fuzzy AHP.

A design method for network attack and defense simulation platform is discussed in this paper. Firstly the component and function of the platform are analyzed. Then Visio second development method is used to construct the virtual network topology. The parsing of virtual network topology is also researched and the relative flow sheet is described. Lastly an example is carried out to test performance of the platform. Simulation results show the effectiveness of the proposed method.

By applying the time-delay control theory to a TCP/RED dynamic model, this note establishes some explicit conditions under which the TCP/RED system is stable in terms of the average queue length. Then, the stability region is discussed. Finally, the results are illustrated by using ns2 simulations, which demonstrates that it is able to choose an appropriate control parameter maxp of RED based on the stability conditions derived in this note, to achieve satisfactory network performance. It is found, by comparison, that this improved performance is better than that of three other typical active queue management (AQM) schemes—the random exponential marking (REM), proportional-integral (PI) controller, and adaptive virtual queue (AVQ) schemes. [ABSTRACT FROM AUTHOR]

To lower down illumination power consumption and enhance lighting effects, smart LED controller and luminance sensors were connected to a WIFI based IOT network, fuzzy luminance control was employed on the IOT net. The schematic topology of the IOT net was outlined. The smart LED controller used the dedicated IOT chip ESP 8266 as the main processor, which was connected to the WIFI network and drove LEDs with PWM signals. The luminance fuzzy control strategy was also implemented on ESP8266 in C language. The fuzzy control process was a typical feedback loop, which took the error (difference between the luminance measured value and the luminance set value) and error change as inputs and calculated the output (the PWM increment) according to fuzzy rules. To test system efficiency, step response experiment and power saving experiment were conducted, proving the system to have good control quality and capable of saving more power by means of intelligent control.