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Network Function of a Circuit

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Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.

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In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...

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Related Experiment Video

Updated: Nov 3, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

SDN-Based Network Slicing Mechanism for a Scalable 4G/5G Core Network: A Kubernetes Approach.

Robert Botez¹, Jose Costa-Requena², Iustin-Alexandru Ivanciu¹

¹Communications Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania.

Sensors (Basel, Switzerland)

|June 2, 2021

Summary

This study evaluates scalable and reliable IoT/M2M traffic management. Edge and cloud deployments show similar resource use, while Kubernetes ensures 4G/5G network function scalability for high availability.

Keywords:

5G EPC IoT Kubernetes NFV SDN cloud computing network slicing

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Area of Science:

* Computer Science, Networking, and Telecommunications.
* Focus on Internet of Things (IoT) and Machine-to-Machine (M2M) communication systems.

Background:

* Managing large volumes of IoT and M2M traffic necessitates evaluating the scalability and reliability of end-to-end systems.
* This includes connectivity, mobile network functions, and data processing applications.

Purpose of the Study:

* To design and evaluate a containerized IoT/M2M application for automated scalability and high availability.
* To analyze solutions for scaling 4G/5G network functions and mobile backhaul for reliable connectivity.
* To validate a scaling algorithm for network slicing using Software-Defined Networking (SDN).

Main Methods:

* Deployment of a containerized IoT/M2M application on edge (balenaCloud) and cloud (AWS EC2, AWS IoT) platforms.
* Resource consumption analysis for edge versus cloud deployments.
* Implementation and testing of Kubernetes for scaling 4G/5G network functions and mobile backhaul.
* Development and experimental validation of an SDN-managed network slicing scaling algorithm.

Main Results:

* No significant differences in resource consumption were observed between edge and cloud deployments of the IoT/M2M application.
* Kubernetes effectively provided scalability and high availability for 4G/5G network functions and mobile backhaul.
* The proposed scaling algorithm for SDN-managed network slicing successfully guaranteed necessary radio and network resources.

Conclusions:

* Containerized IoT/M2M applications can be deployed effectively on both edge and cloud environments with comparable resource efficiency.
* Kubernetes is a viable solution for achieving scalability and high availability in 4G/5G network functions and mobile backhaul.
* SDN-based network slicing with a dynamic scaling algorithm ensures end-to-end high availability for critical IoT/M2M services.