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Kamiš, A. et al. (2026). Development of a Cloud-Based WebRTC VoIP Application Using the Docker Platform for an Educational
Environment, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 14(1), 11-21.
Original scientific paper
Received: February 07, 2026.
Revised: March 25, 2026.
Accepted: April 29, 2026.
UDC:
004.42WEBRTC VOIP
37.018.43:004.9
10.23947/2334-8496-2026-14-1-011-021
© 2026 by the authors. This article is an open access article distributed under the terms and conditions of the
Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
*
Corresponding author: alen@vub.edu.ba
Abstract: The development of real-time communication systems has become increasingly important for educational
institutions seeking flexible, scalable, and cost-effective digital learning environments. This paper presents the design, imple-
mentation, and performance evaluation of a cloud-based WebRTC Voice over IP application deployed through Docker con-
tainer technology and integrated into an educational e-learning system. The proposed solution enables secure browser-based
audio and video communication between instructors and students, as well as among students, without requiring additional
plugins or native software installation. The application architecture is based on multiple containerized microservices, including
database, WebSocket, Apache, and Nginx components, hosted within the Microsoft Azure cloud environment. To assess the
efficiency of the proposed model, performance testing was conducted across three deployment infrastructures: bare-metal
server, virtual server, and Docker-based platform. The evaluation included application deployment time, startup time, system
restart time, and response time under different numbers of concurrent sessions. The results indicate that the Docker-based
implementation achieved the best overall performance, with substantially shorter deployment and startup times and lower
response latency compared with both bare-metal and virtualized alternatives. These findings confirm that containerized
WebRTC infrastructure can improve scalability, maintainability, and responsiveness in educational communication systems.
The study contributes a practical implementation model for integrating real-time VoIP and video communication into e-learning
platforms, particularly for institutions seeking open-source, cloud-ready, and resource-efficient communication solutions.
Keywords: Docker, Container, WebRTC, Educational Institution Software, Voice over IP.
Alen Kamis
1*
, Aleksandar Zakic
2
, Gradimirka Popovic
3
, Milija Bogavac
4
, Dejan Milic
5
, Bogdan Ignjatovic
6
,
Lakhmi C. Jain
7
1
The College of Service Business, East Sarajevo - Sokolac, Bosnia and Herzegovina, email: alen@vub.edu.ba
2
Alfa BK University, Faculty of Information Technology, Belgrade, Serbia, email: aleksandar.zakic@alfa.edu.rs
3
Kosovo and Metohija Academy of Applied Studies, Leposavic, Serbia, email: gradimirka.popovic@akademijakm.edu.rs
4
MB University Belgrade, Faculty of Business and Law, Belgrade, Serbia, email: milija.bogavac@ppf.edu.rs
5
National Security Academy, Belgrade, Serbia, email: dejanmilic00@gmail.com
6
Hiting Frankfurter, Groß-Gerau, Germany, email: bokiexe@gmail.com
7
University of Piraeus, Piraeus, Greece, email: jainlakhmi@gmail.com
Development of a Cloud-Based WebRTC VoIP Application Using the
Docker Platform for an Educational Environment
Introduction
The accelerated development of technology has enabled us to eliminate expensive international calls
by using alternative solutions to telephony. Now we have Voice over IP (VoIP) applications that represent tel-
ephone calls over the Internet. During the COVID-19 pandemic, the use of VoIP applications was at its highest
level. These applications were used for various purposes, such as school lectures, business meetings, remote
work, and more. The constant development of technology and the popularization of Internet usage among the
masses, for both business and personal purposes, contribute to the expansion of VoIP. Additionally, there is a
growing need for multimedia services and communications.
However, VoIP communication still occupies only a small portion of communications today. The
future of VoIP lies in the capabilities of the new and more advanced applications, where voice is just
one piece of information. VoIP applications are usually designed as client-server applications, such as
Microsoft Teams or Google Meet. These commercial versions are hosted in the cloud, physical, or virtual
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servers within a local infrastructure. Due to a large number of dependencies that these applications use,
their actual startup takes a long time.
The aim of this research project was to build a VoIP application based on the WebRTC (Web Real-
Time Communication) protocol, which will connect people in real-time.
Application code is provided for free, so it may be built upon and possibly integrated with other ap-
plications. Since WebRTC is a client-server technology usually installed on physical and virtual servers,
we wanted to go with Docker as an underlying platform for our application (Hartono et al., 2025).
The expectation was that it would perform better than certain traditional implementations, such as
bare-metal and virtual installations. The application design uses multiple software containers (microser-
vices), thereby optimizing the application performance, startup time, as well as improving the quality of
maintenance procedures.
After creating the application, we performed the necessary measurements, and compared the
speed and performance of our implementation with the mentioned traditional ones. During the implemen-
tation, Docker was used with an initial setup on the Windows 11 operating system, where all the contain-
ers were deployed. After the successful implementation of the development platform, the containers were
migrated to Microsoft Azure cloud to serve as the basis for the production platform.
In the following chapters, the essential concepts and features of Docker are explained, along with
the differences among the traditional infrastructures (i.e., virtual and physical servers). This serves as
the theoretical background for demonstrating the technologies behind our WebRTC-based application
(Castro-Castaño et al., 2026). This application allows us to reach a significant performance increase for
VoIP applications, as evident by its implementation on the Docker platform.
Related work
Since data is one of the most valuable assets of the modern world, it is highly important to protect
it. Once transmitted over the public network, audio and video data become vulnerable to cyberattacks.
In their research paper, Chithra and Aparna have proposed an innovative method (a blockchain-enabled
dual level security scheme) of transmitting video data over a secret channel, thereby adding a security
aspect to the transmission of audio/video data (Chithra and Aparna, 2023).
The importance of their novel solution for this work lies in the security hardening of our web applica-
tion for VoIP calls, based on the open-source WebRTC technology.
Although the experimental analysis conducted by Chithra and Aparna was mainly focused on video
data, the proposed solution can potentially be applied to voice data as well. This is one type of data pro-
cessed by our WebRTC-based application, and the possibility for future enhancements lies in the applica-
tion of the mentioned security scheme on that data.
Since the research project represented in this paper brings novelty and is open for further develop-
ment, it is relatively difficult to find a similar solution, especially with the Docker platform in use.
Docker software
Docker is software that is supported on both Linux and Windows operating systems. It is a tool
designed for creating, deploying, and running applications using containers. Its use is of greatest benefit
for developers who can choose their preferred platform and develop on it without worrying about the op-
erating system on which their application is going to run. Docker offers manageable virtual environments
called containers. A single Docker instance can have multiple containers, each operating independently
and in isolation from one another.
Considering that Docker uses virtualization to create containers, the concept strongly resembles a
virtual machine. Although both approaches provide isolated runtime environments, there are significant
differences in how they operate. The obvious difference is that Docker consumes fewer resources, is
faster, and lightweight on the system (Docker, 2024). The advantages of this model are manifold, but the
most significant benefit is application compatibility. In practice, this means that an application developed
within a container will function seamlessly on any Docker, regardless of compatibility issues. Packaged
within such an isolated environment (container), the application is easier to develop, maintain, and use.
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Kamiš, A. et al. (2026). Development of a Cloud-Based WebRTC VoIP Application Using the Docker Platform for an Educational
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The main Docker components are: Docker platform, Docker engine, Docker architecture (Docker client,
Docker daemon, Docker registry), Docker objects (images, containers, services), and Docker Hub.
Docker platform
The Docker platform is a set of tools that enable us to manage the lifecycle of containers. This
platform was chosen because it allows for creation, management, and maintenance of applications in
microservices that are packaged in software containers. The containers are isolated from each other.
They contain their own software, libraries, and configuration files. They communicate with each other via
precisely defined channels. Docker is essentially an approach to virtualization where the setup is less
complex. For the Docker platform to work, there needs to be a basic operating system and software on the
server that enables the use of containers – Docker Engine. On the other hand, for virtualization platforms,
an appropriate hypervisor is required, and each individual virtual machine must have its own operating
system installed on which the desired application runs (Lv et al., 2026). Virtual machines are therefore
more flexible because they do not depend on the underlying host operating system. But software contain-
ers are significantly less complex and more efficient in resource utilization, allowing for 4 to 6 times more
containers to run on the same server than virtual machines. All containers are managed by the operating
system kernel and are therefore lighter than virtual machines.
Docker engine
The Docker Engine is a client-server application with the following components:
• Server, which is a long-running process called a daemon. This process runs in the background and
responds to requests sent to it.
• REST (Representational State Transfer) API (Application Programming Interface), which specifies inter-
faces that programs use to communicate with the daemon and send it instructions.
• CLI (Command Line Interface).
The command-line interface uses the Docker REST API to control and communicate with the Docker
daemon through scripts or direct CLI commands. The daemon creates and manages Docker objects such
as containers, networks, and disks. Figure 1 illustrates how Docker components are interconnected.
Figure 1. Components of Docker Engine (Docker, 2024)
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Docker architecture
The Docker architecture is based on the client-server model and defines the operation and relation-
ships of the basic Docker components. In Figure 2, the connections between individual components in the
client-server architecture are shown. The client and daemon may or may not be on the same server; as
needed, the client can be connected to the daemon remotely.
Figure 2. Docker architecture (Kumar, 2024)
The Docker client is the primary means of user interaction with Docker. Using commands via the
command-line interface, the client forwards them to the Docker daemon over an API. The daemon is a
server process that runs continuously in the background, monitors the REST API for incoming command
processing requests, and executes them. Software images for Docker must be stored at a specific loction
for easy access. This location is called the Docker registry. Docker Hub is an example of a public registry
that anyone can use, and Docker is configured by default to use Docker Hub. However, users can use
their private registry as needed.
Docker objects
Objects include images, containers, services, and volumes. Objects are primarily generated by the
Docker daemon. On the other hand, images are read-only system files containing instructions for creating
a container that can run an application. A Dockerfile contains simple commands executed by the daemon
to create and run images. Each command in the Dockerfile creates a separate layer within the image.
When we modify the Docker file to change the image, only those layers containing the change
are affected. This is the main reason why images consume much fewer resources than virtual machines.
When we talk about containers in the context of applications and software, we can compare them
to the real shipping containers. Before being standardized, shipping goods was a demanding and costly
process. Depending on the type of goods and the shipping method used, it was necessary to adjust the
packaging method. Standardizing containers balanced the way goods are shipped, regardless of type,
shape, size, and mode of transport. The amount of work was reduced with the simplification of the pro-
cess, leading to significant time and cost savings (Jangla, 2018).
A similar principle applies to software containers. We have an image that is run inside the container,
and the container only includes what is necessary to run the application. We can then transport and
run this container anywhere. Instead of installing the entire operating system and all the accompanying
software, the container typically contains only the following components: the application itself, necessary
libraries, components on which the application depends (dependencies), as well as configuration files and
folders (shown in Figure 3). The application thus becomes independent of the type of operating system
distribution and infrastructure on which it is run.
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Figure 3. Architecture of a container
Containers are often associated with, or even confused with, the concept of virtual machines. Virtal
machines run within a virtualization software and actually represent separate operating systems within the
host. Therefore, they have their own libraries and programs, but also occupy several gigabytes of memory
space (Shih et al, 2021). On the other hand, containers are essentially just isolated environments within
the host operating system and they contain their own libraries for specific processes and applications,
making them much smaller when stored in memory (Kul et al, 2024). Below in Figure 4 is a diagram il-
lustrating the technical differences between virtual machines and containers (Jones, 2018).
Figure 4. Containers vs. virtual machines
Services allow users to scale containers across multiple Docker instances. In this way, multiple
containers can work together via the Docker API and exchange data among themselves to perform a task.
To the end-user, it will appear as if all the work is being done by a single application.
Docker Hub
Docker Hub is the primary location for hosting Docker Images. It is a cloud-based public registry
on which images can be stored and from which they can be pulled. It serves as a centralized distribution
and discovery point for images. Users can buy or sell images on Docker Hub, or distribute them for free.
Images can be searched using either the Docker Hub interface or the CLI.
WebRTC web application
WebRTC is a free open-source project that provides web browsers and mobile applications with
real-time communication via the application programming interface (API). It enables audio and video com-
munication within web pages, allowing direct peer-to-peer communication, and eliminating the need for
installing plugins or downloading native applications (WebRTC Code Samples, n.d.).
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The project is a web-based application that enables the establishment of video calls using We-
bRTC open-source code. Architecturally, the web application is implemented using containers hosted on
Microsoft Azure. As part of the application, a user registration and login portal has also been developed,
enhancing the application’s security. The application code is freely available to all interested parties. The
goal of developing such an application is to contribute to the community by allowing users to reduce their
communication costs without investing in the development of similar applications. It will primarily help
smaller companies and businesses that do not have enough resources or manpower to spend time on
developing the application. The developed WebRTC platform can be integrated into any application that
has a developed API interface. Architecture of the WebRTC application is shown in Figure 5.
Figure 5. Architecture of the WebRTC application (The Past, Present, and Future of WebRTC, 2022.)
WebRTC is an open-source project that enables real-time audio, video, and data communication via
web and native applications. In our project, we have utilized a portion of WebRTC for voice communication.
WebRTC has several JavaScript APIs, out of which the most popular ones are:
• getUserMedia: enabling the use of input functions (camera and microphone);
• MediaRecorder: audio and video recording;
• RTCPeerConnection: audio and video streaming between users;
• RTCDataChannel: data streaming between users.
For a WebRTC web application to work properly, we need a signaling service, commonly referred
to as signaling or „signaling server“ (Signaling and Video Calling - Web APIs | MDN, 2024.). WebRTC
uses RTCPeerConnection for streaming data communication between browsers, but a mechanism for
coordinating communication and sending control messages is also required. WebRTC does not specify
signaling methods and protocols. As part of this project, we can use Socket.IO for message exchange,
but there are other alternatives. For a WebRTC application to establish a call, its clients must exchange
the following information: session control messages for opening or closing communications, error mes-
sages, media metadata (codecs, codec settings, bandwidth, and media types), key data for establishing
secure connections, and network data (i.e., host’s IP address and port as seen by the external side of the
network) (Almousa et al, 2021).
The signaling process requires a mechanism for clients to exchange messages back and forth.
This mechanism is not implemented by the WebRTC API itself but must be created independently. We-
bRTC is designed to operate on a peer-to-peer connection basis, allowing users to connect in the most
direct way possible. However, WebRTC is built to support the latest networking technologies, meaning
that client applications can traverse NAT gateways and firewalls if peer-to-peer call establishment fails.
Call encryption is mandatory for all WebRTC components, and its JavaScript APIs can only be used in
secure communication via Hypertext Transfer Protocol Secure (HTTPS) connection.
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Application design
The following image (Figure 6) shows a schematic representation of Docker containers on a local
computer and the Microsoft Azure platform.
Figure 6. Design of the WebRTC application
WebRTC application is completely free and can be downloaded with the accompanying code on
GitHub (Alenkamis, 2022.). The application on Microsoft Azure consists of four containers (“DB”, “Web-
socket”, “Nginx”, and “www”), and one Linux virtual machine.
The DB container is a part of the web application where a MySQL database, necessary for the
website, is located. Within the DB container, a database named “web” has been created. Inside the “web”
database, there is a table called “users”, where users who register on the web application are stored. The
websocket container is a part of the web application that provides support for working with websockets,
since the PHP programming language does not natively support the WebRTC platform. Due to excellent
native support for websockets, Node.js was used for the message exchange microservice between com-
ponents, thereby avoiding undesired effects. The configuration for websockets in Node.js consists of the
server-side and client-side parts. The server-side configuration is located in the “websocket” container,
while the client-side configuration is located in the “www” container. The www container is crucial for the
web application because it contains the Apache server. From the Docker configuration files, it can be
concluded that the website is located in the /var/www/html folder. The following files, necessary for the
operation of the web application, are located inside the html directory: call.php, functions.php, index.
php, login.php, logout.php, registration.php, script.js, and socket.io.js. The Nginx container serves
as the frontend web server that users first encounter when accessing the WebRTC application. Upon
connection attempt, users connect to the Ngnix Web server via TCP port 443, which is a standard for
HTTPS sessions. A Let’s Encrypt certificate is implemented directly on the container to prevent users from
encountering errors when opening the application (Ardi et al, 2025).
The following image (Figure 7) depicts the entire operation of the WebRTC application, from ac-
cessing the website to establishing a VoIP call to another user.
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Figure 7. Schematic representation of video call establishment via the WebRTC application
Results of WebRTC application performance testing
The development of the WebRTC platform on Docker infrastructure has opened the possibility of
measuring and testing performance across three different systems. The first system is a developed plat-
form based on bare-metal infrastructure (Ubuntu Server 22.04 version), the second platform is a virtual
server (Ubuntu Server 22.04 version), and the third is the WebRTC platform on Docker infrastructure.
All measurements were conducted on the same server with identical specifications: Dell Power-
Edge R660, Intel Gold 6139 processor, 256 GB RAM, 4 x 1.92 TB SSD disks, and 2 x 10G network adapt-
ers. Performance measurements were carried out using iPerf and nPerf software tools, which provide the
necessary capabilities.
iPerf is a powerful tool that allows the testing of network throughput, latency, and packet loss within
a mesh network. iPerf enables the generation of network load to assess the maximum data transfer speed
and identify potential network bottlenecks (Garcia et al, 2017). This tool provides detailed reports and
measurement results, allowing us to identify and resolve issues in the application’s operation (Yadav et al, 2018).
nPerf is a tool that also tests data transfer speed and latency within the application to gain insight
into its performance. nPerf provides detailed results that help analyze connection quality and identify po-
tential problems. Whether in the implementation, maintenance, or optimization phase of the application,
nPerf can help in the better understanding of its performance and quality improvement (Marinković et al, 2021).
The research and WebRTC application testing results are presented in the following table (Table 1).
It provides insight into application performance after each type of test given in the table is applied across
three different platforms.
Table 1. Results of WebRTC application performance testing on three different platforms
Type of test
Bare-metal
WebRTC
Virtual server
WebRTC
Docker plat-
form WebRTC
Initial application deployment (minutes) 120 35 6
Application startup (seconds) 106 41,2 7
System restart (seconds) 120 50 11
Application response without any calls (milliseconds) 89,3 67,1 17,6
Application response with 5 concurrent sessions (milliseconds) 102,4 77,5 21,2
Application response with 10 concurrent sessions (milliseconds) 124,2 88,9 24,7
The following graph (Figure 8) shows the loads in application response during a specific number of
calls, with the values expressed in milliseconds.
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Figure 8. Application load measurement chart
Using Laplace’s matrix and Hertz’s formulas for loads (without startup and deployment data), we
arrive at the application performance results showing that the bare-metal platform (physical) is convinc-
ingly the slowest, while the virtual machine platform is 24.8% faster than it. However, ultimately, it can be
said that the Docker platform is the fastest in the test and has the best performance, being 81.3% faster
than the bare-metal platform and 72.3% faster than the virtual one.
WebRTC Integration within the E-Learning System
The developed WebRTC application has been successfully integrated into our existing e-learning
system, enabling secure, real-time communication between instructors and students. The application
uses Web Real-Time Communication WebRTC technology, which allows direct peer-to-peer exchange
of audio and video data within a web browser, without the need for additional plugins or software. This
approach enables instructors to communicate with students in real time, as well as interact with each
other, significantly enhancing the interactivity of lessons and supporting dynamic educational processes.
Furthermore, students can communicate among themselves, which further promotes collaboration, team-
work, and the collegial exchange of knowledge.
In the professional literature, WebRTC is increasingly recognized as a superior technology for
real-time communication compared to traditional infrastructures based on virtualization or physical serv-
ers, due to its peer-to-peer architecture and low latency. Peer-to-peer communication allows direct data
exchange between end users, significantly reducing the load on central servers and infrastructure, which
contributes to faster and more efficient media transmission (Mahmoud and Abozariba, 2024).This ap-
proach does not require complex virtualized or physical server infrastructures, minimizing latency and im-
proving user experience, particularly in real-time scenarios such as video calls and interactive discussions.
Because of these advantages, WebRTC is increasingly used in modern educational platforms and
communication systems, as it combines low latency, scalability, and efficient use of network resources
without the need for large server farms or complex virtualized environments (Mahmoud and Abozariba,
2024). In our case, the platform is already integrated into the e-learning system and enables immediate
and smooth interaction between instructors and students, as well as among students themselves, sig-
nificantly improving the quality of the learning process and supporting reliable real-time communication.
Conclusions
The work briefly describes the mechanisms of Docker infrastructure and explores the operation of
the created WebRTC-based application for VoIP and video communications. WebRTC is an open-source
platform, and as such, it is very interesting for use. The goal of developing this application is to contribute
to the community by enabling users to reduce their communication costs, without investing in the devel-
opment or purchase of similar applications. Primarily, it will assist smaller companies that lack sufficient
resources and manpower needed for their development.
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Environment, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 14(1), 11-21.
The infrastructure of the application is built on the Docker container platform. This platform emerged
in 2013 and immediately became a popular choice for development environments. Docker as a platform
is increasingly being used for production systems due to the convenience of microservices. It has its
advantages in terms of: a quick application startup, segmentation features that make it less susceptible
to attacks, and the facilitation of simplified repairs and servicing. After testing the performance of the
proposed WebRTC-based application with varying degrees of network load and using different types of
tests, we have obtained the results in favor of the Docker platform implementation. It has by far shown the
best performance under any type of test, whether it be the time needed to deploy the application, or its
response to an increasing number of concurrent sessions (calls).
In conclusion, it is expected that the Docker container platform will continue to progress and grow
in the future, and that in the coming years many applications will be based on this platform. We sincerely
hope that our diligent work on this highly performant VoIP application will reach end users who will gladly
use it in the future.
Acknowledgements
The authors thank the managements of Alfa BK University and MB University for their support in
the research process and technical preparation of the manuscript.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial,
or not-for-profit sectors.
Conflict of interests
The authors declare no conflict of interest.
Data availability statement
The data supporting the reported results in this study are contained within the article itself.
Institutional Review Board Statement
Not applicable.
Author Contributions
Conceptualization, A.K., A.Z. and B.I.; methodology, A.K. and M.B; software, AK, B.I. and A.Z.; for-
mal analysis, A.K., G.P. and L.C.J.; writing—original draft preparation, A.K., M.B. and A.Z.; writing—review
and editing, A.K, and L.C.J. All authors have read and agreed to the published version of the manuscript.
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