Methods of Spline Functions in Solving Problems of Telecommunication and Information Technologies

Abstract

The solution to problems of telecommunications and information technologies using spline approximation and spline extrapolation based on real and complex spline functions is considered. The use of spline approximation for solving problems of signal recovery and self-similar traffic, processes of functioning of telecommunication nodes and networks is shown. It is proposed to use spline extrapolation based on various types of real spline functions to solve the problems of predicting the characteristics of self-similar traffic and maintaining QoS characteristics during its maintenance. It has been established that to predict the real-time telemetry traffic of IoT devices, it is advisable to use spline extrapolation based on the cubic Hermite spike, which ensures the required forecasting accuracy and prevents network overloads, especially under conditions of network load limit. To solve the problem of user positioning in the radio access area, the use of complex plane spline functions is considered. The use of the methods of real and complex spline functions allows for obtaining the results of improving the quality of service in a telecommunications network and ensuring the scalability of the obtained solutions. To identify and predict DDoS cyber-attacks, a spline extrapolation method is used. The use of parametric splines in the problems of information technology, namely, the construction of curves and surfaces in 3D modelling, is proposed.

Keywords

• spline approximation
• spline extrapolation
• real spline functions
• complex spline functions
• cubic spline function
• quadratic spline function
• hermite cubic spline
• signal recovery
• forecasting
• self-similar traffic
• iot device telemetry traffic
• qos characteristics
• local user location
• ddos cyber-attacks
• parametric splines
• 3d modelling