Serverless computing is a paradigm that enables the execution of code without provisioning or managing servers. It ofers benefits such as scalability, cost-eficiency, and ease of development for cloud-based applications. In this paper, we explore the potential of serverless computing for supporting data processing in open learning and research environments. We propose a concept of a hybrid serverless cloud, which combines diferent types of cloud services to provide access to various tools and resources for learners and researchers. We present a case study of wave files processing using a lambda function, which demonstrates the feasibility and efectiveness of our approach. We also discuss the challenges and opportunities of integrating serverless components within open systems of learning and research. Finally, we present a vision of a cloud-based open learning and research university environment that leverages serverless technologies to enhance the quality and accessibility of education and research.
Cloud-based learning and research environments are emerging as a key paradigm for
modernizing the educational process in higher education and fostering open science within the
European Research Area [
Cloud computing ofers various models, such as IaaS, PaaS and SaaS, that can facilitate learning and research data processing. By abstracting resources and providing simple automation tools, modern cloud platforms simplify many routine tasks, such as installation, maintenance, backup, security, and more [5, 13]. Moreover, in the context of open science, open data and big data processing are essential. To meet the requirements of open science systems design, large amounts of data need to be available and accessible for joint processing by the community of scientists [5]. Therefore, cloud computing platforms can serve as a reasonable framework to support open learning and research processes, both in terms of managing and processing large amounts of data and making them available for collaborative use [5].
The computing capacity is crucial for processing and retrieving large amounts of data, which
are needed at most stages of the research process, such as data collection, representation,
visualization, analysis, interpretation and discussion. A possible way to save resources and
provide flexible use of the cloud-based infrastructure is to use lambda functions within the
serverless settings. This leads to the notion of Function-As-A-Service (FAAS) as a promising
cloud-based model [
The applications and evaluation of serverless computing in diferent areas are among the
current issues considered nowadays, for example for machine learning [
The article aims to consider and evaluate a hybrid cloud-based serverless architecture as a possible open learning and research platform to support data processing and research collaboration. The main idea is that design and development of learning and research environment due to the proposed approach will result in more eficient use of the cloud-based resources, better access to learning and research data and collaboration support. The case study of the sound signal processing as a possible example of serverless approach application for learning and research is considered.
The paper introduces the main concepts and terms related to the design and development of university cloud-based learning and research environment (LRE), based on the principles of open science, open education, and cloud-oriented systems, as proposed by Bykov and Shyshkina [4].
The LRE of a higher education institution is defined as an environment that leverages the virtualized computer-technological infrastructure (corporate or hybrid-based) to support the content-technological and information-communication functions of learning and research activities [4].
Serverless technologies are adopted to build applications that require dynamic and
unpredictable computing resources. The serverless hybrid cloud architecture enables the deployment
of lambda-functions [
Figure 1 illustrates the configuration of the serverless application architecture.
The proposed approach is to access lambda-functions through API Gateway, avoiding server management as lambda-functions return the values in static HTML format, which are stored and retrieved on S3-bucket, and can be further processed.
This approach allows the user to access specific electronic resources and computing capacities hosted on a hybrid serverless architecture from any device with an Internet connection.
The advantage of this approach is that it provides flexibility and scalability for learning or research processes that need computing resources for special purposes that may arise occasionally. For example, in the course of an experimental research, big data processing may be needed that require high computing power for a short time. It may be ineficient to maintain and manage a cloud server for these purposes. However, by using lambda-functions, the learner or researcher can access a server with powerful processing capabilities without deploying it every time as the function is needed. The necessary resources can be supplied more eficiently on demand.
The cloud-based LRE was implemented at the Institute for Digitalisation of Education of the NAES of Ukraine as part of the research projects and pedagogical experiments conducted from 2012 to 2017. During this period, various cloud-based services were integrated into the research and educational process to support open education and open science [4].
In 2018, the V4+ Academic Research Consortium Integrating Databases, Robotics and Language Technologies was established, which aimed to address regional issues related to EU ICT research priorities. The consortium used the following cloud-based components for collaborative work: • The BOX Cloud shared work-space – a cloud storage and transfer service that connected the researchers’ computers and allowed them to share documents. • The virtual machine with Windows 10 – a remote desktop that provided a common computing environment for the partners [5].
The cloud-based components that were developed and tested during this period were also applied in the learning process. The course “Cloud Computing Technologies’’ was designed and introduced in National University of Life and Environmental Sciences of Ukraine for training computer science bachelors. The students learned how to build cloud-based components on virtual machines using AWS and Azure platforms. The methodology of open learning and research platform implementation proved to be efective.
The next step of the research was the creation of the serverless hybrid cloud architecture to support collaborative research with Kyiv Glushkov Institute of Cybernetics of the NAS of Ukraine. The goal was to use lambda-functions for sound signal processing and analysis. Figure 2 shows an example of a sound signal oscillogram generated by a lambda-function.
The serverless environment was used for the following tasks: 1. A Python-based web application was created using the Flask framework and tested on localhost.
2. A user account with necessary permissions was created in the AWS console to secure future applications. An S3 bucket and an EC2 server were also created in the AWS console. The working folder with the Python script (or another compatible language for AWS Lambda) was uploaded to S3. 3. To enable the processing, one or more layers with the required libraries were attached to the lambda-function. The libraries were installed in a virtual environment on the EC2 server. An additional layer was created from this environment. AWS Lambda also provides some freely distributable layers that can be used in future applications. 4. A YAML file was created using CloudFormation tool to specify the available resources for the application. The YAML file created a separate role for working with the future application.
4.1 Using this role, a lambda-function was created, and its code was downloaded from the zip file created in S3.
4.2 Using this role, an API Gateway was created to allow calling the lambda-function from a browser. 5. The application was debugged and tested.
Using this sequence of steps, a hybrid environment with lambda-function was created and tested for sound signal processing.
The paper has presented the rationale and the methodology for introducing cloud technologies in the educational and research process of higher education institutions, as well as the design and implementation of the learning and research environment based on these technologies. The paper has demonstrated how cloud technologies can enhance the access to electronic educational resources, improve the eficiency of ICT infrastructure, and support open education and open science principles. The paper has also proposed a novel approach for using serverless technologies to provide cloud services for data processing, visualization and retrieval, which is a relevant and promising area of development and modernization of the university open learning and research environment.
The paper has reported the experience of developing and applying various cloud-based components for educational and scientific purposes based on the proposed architecture of the hybrid cloud-based environment with lambda-functions. The paper has shown how lambdafunctions can enable flexible and scalable computing resources for learning or research tasks that require dynamic and unpredictable computing power.
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