Development and analysis of models for service migration to the MEC server based on hysteresis approach

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Online video services are among the most popular ways of content consumption. Video hosting servers have a very high load every day, which we propose to reduce by migrating the application with the video content in demand to the local Multi-access Edge Computing (MEC) server of the target. This makes it possible to improve the quality of services (QoS) provided to users by reducing the transmission delay. Therefore, an architecture has been proposed that allows, at times of increased demand for the same video content, to migrate the video service application to the edge servers of the network operator. To evaluate the performance of this approach, a mathematical model was developed in the form of a queuing system. The results of the numerical experiment make it possible to optimize the time of using local MEC servers to provide video content.

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1. Introduction In the modern world, demand for various multimedia services is increasing every year. For example, services for providing online video content are very popular and allow us to access information in a simple way anytime and anywhere from a device with Internet connection. However, with the growth in the amounts of video content and an increase in its demand, requirements for the quality of the services (QoS) are as well increased. Video service providers, in turn, are trying to reduce transmission delays and improve the quality of the video, which increases the size of video files and requires more channel bandwidth to be transmitted to the end user. The idea of decentralized content placement by a video service provider is not new. In most countries, large cities, operators use the services of geographically distributed content delivery network architecture (CDN). It allows for the video data delivery optimization by using servers, located much closer to the end user. Multi-access Edge Computing (MEC) servers utilization allows service providers to optimize the transmission process by placing the user-requested content on servers not only within a specific city, but also within a specific district or street. In the same way it solves the problem of high load on transport networks, which is beneficial for the video service provider, who gets the opportunity to provide high-quality content. Thus, the transport network operator can reduce network operation costs and receive additional profit for renting edge computing servers. MEC introduces the cloud computing capabilities and IT service environment at the edge of the mobile network. The network edge includes base station infrastructure and data centers close to the radio network. In work [1], the authors have presented a classification of application models and a study of the latest models of mobile cloud applications. In [2], a brief analysis of the requirements for mobile cloud computing (MCC) have been done, the main applications and upload technologies, the classification of contexts and context management methods. In [3], the authors have provided an overview of the definitions, architectures, and applications of MCC, as well as common problems and some existing solutions. In reference [4] a study of existing work on MCC platforms and intelligent access schemes can be found. Another group of scientists in [5] has investigated a detailed taxonomy of mobile cloud computing based on key issues and approaches to address them. Work [6] has introduced a comprehensive overview of the current MCC authentication mechanism and compared cloud computing. The authors in [7] have studied a taxonomy of MEC based on various aspects, including its characteristics, access technologies, applications, purposes, etc. Reference [8] has categorized deployed applications in MEC according to the technical metrics of MEC and the benefit brought by MEC to network stakeholders. A discussion of threats and security in boundary paradigms, as well as possible solution for each specific problem, can be found in [9]. In [10], representative applications and various aspects of the study of fog computing problems are highlighted. An overview on emerging security and privacy issues in fog computing, as well as cloud computing issues is closely discussed in [11]. A study of web caching and prefetching methods for improving network performance, as well as a classification of web caching policies, can be found in [12]. A description of the advantages and disadvantages of cache replacement strategies can be found in [13]. The model of interaction between the edge computing based on Software-defined networking (SDN) and Network functions virtualization (NFV) technology and the cloud computing in the next generation Internet of Things (IoT) is presented in [14]. In [15] authors consider the usage of a MEC server for processing home health monitoring data locally, making it possible to optimize the system-wide cost and the number of patients benefiting from MEC. 2. System description As described above, the consumption of online video content is growing every year, since any information presented by a video sequence with sound accompaniment makes it easier to perceive or just spend leisure time. Requests for the provision of such services, especially of an entertainment nature, do not have a constant intensity, but in most cases occur in avalanche bursts at different times or days. For example, in the evening, most people come home from work and watch their favorite series, talk shows, etc. This section describes the process of providing online video and possible scenarios for optimizing content delivery to users. Figure 1. Network architecture for connecting users to a video content service The figure 1 shows a diagram for providing online video services to users. On the left side the service provider’s servers are shown. These servers host and process videos to provide the users on demand. On the right is the operator’s last mile access network, which provides end users with access to the global network, and, in particular, connections to the service provider’s servers. This network is presented in more detail and consists of - 1st segment - it includes all elements of the operator’s network core and, is responsible for routing traffic within the network and outside of it; - 2nd segment - it consists of terminal switching devices for wired connection of users and/or base stations of a cellular network for a wireless connection of mobile users (this segment is variable and changes depending on the task). Between the service provider and the network operator, there are backbone operators and traffic exchange points, which are shown as a direct connection, since they mainly just make data transfer delay, and are also not the main beneficiaries in optimizing the process of providing a service to users. We consider the process of providing a service to users. The very process of establishing a connection for an online video service has been described and studied in detail in work [16]. Thus it is proposed to focus on the main points presented in the figure 2: 1) a user in the carrier’s network sends a video viewing request to a service provider; 2) the service provider processes the request and sends a connection confirmation to the user; 3) a connection is established and the user starts watching the video. The network operator serves several zones (districts) with

About the authors

Dmitry S. Poluektov

Peoples’ Friendship University of Russia (RUDN University)

Author for correspondence.
ORCID iD: 0000-0002-4246-8483

postgraduate student of Department of Applied Probability and Informatics

6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation

Abdukodir A. Khakimov

Peoples’ Friendship University of Russia (RUDN University)

ORCID iD: 0000-0003-2362-3270

Researcher of Department of Applied Probability and Informatics

6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation


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Copyright (c) 2022 Poluektov D.S., Khakimov A.A.

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