Study of the Operation Process of the E-Commerce Oriented Ecosystem of 5Ge Base Station, Which Supports the Functioning of Independent Virtual Network Segments

Abstract

According to specifications, flexible services for traffic management should be implemented within the 5G platform in order to improve its efficiency, which is and will remain an actual task. For the first time, the article presented here proposes a mathematical model for the operation process of an e-commerce-oriented ecosystem of a 5Ge base station, the information environment of which supports the operation of independent virtual network segments that provide terminal–segment information interaction services. In contrast to existing models, the presented model describes the studied process as a multi-pipeline queuing system, the inputs of which are coordinated with the flows of requests for communication with the relevant virtual network segments. The distribution of the total resources between the weighted virtual network segments in the simulated system is dynamically conducted by the appropriate software control mechanism. It considers the address intensities of new incoming requests and the maintenance of received incoming requests, but throughout the scale of the information environment of the 5Ge base station ecosystem. Based on the created mathematical model, a functional algorithm for the forced termination of an active terminal–segment information interaction session in the overloaded virtual network segment and the control mechanism of the distribution of the released system resources between other virtual network segments that takes into account the degree of their overload are formulated. The simulation and computational experiments showed that the implemented forced termination algorithm and system resource management mechanism allow the 5Ge base station to continue receiving incoming requests despite the overload of individual virtual network segments. It is empirically shown that the proposed services are effectively scaled concerning the value that is generally available for the distribution of the number of system resources and the allocation method within the guaranteed amounts of system resources for individual virtual network segments.

Investigation of the competitive nature of eMBB and mMTC 5G services in conditions of limited communication resource

“…In it, the eMBB service supports multimedia streams from surveillance cameras and the mMTC service supports the operation of a sensor network, the sensors of which are located at traffic lights in the city. A detailed description of the network architecture used by the authors for experiments was made earlier in 27 , 31 , 32 .…”

Modeling a session of subject-system interaction in a wireless communication infrastructure with a mixed resource

“…Separately, we note the research direction of analyzing the process of functioning communication systems with different mixed types of traffic [ 8 – 16 ]. The results of such studies are summarized in the form of analytically determined metrics of qualitative indicators, calculating which can assess the effectiveness of the profile application of specific instances of communication systems.…”

An efficient cyber‐physical system using hybridized enhanced support‐vector machine with Ada‐Boost classification algorithm

“…Cyber-attacks are one of the consecutive evolving complications with emphasized algorithms with enhanced software programs, hardware set, and other network topology. 1 These types of malicious-cyber-attacks expose crucial security problems which necessitate for reliable, flexible CPS model. In the present decade, the process of automation is essential in this modern world.…”

“…An interactive methodology for network intrusion visualization three-dimensionally facilitates the employment of a supervised enhanced machine-learning model. 1 Hence the study is focused to concentrate on this concept to provide a representation of different network-traffic categories relationships. The ML techniques would differentiate normal network data and the abnormal intrusion data at a higher accuracy level.…”

“…This machine learning approach is capable to provide automation in detection mechanisms and determine traffic patterns. An interactive methodology for network intrusion visualization three‐dimensionally facilitates the employment of a supervised enhanced machine‐learning model 1 . Hence the study is focused to concentrate on this concept to provide a representation of different network‐traffic categories relationships.…”