Citation: Osei-Mensah, E.; Thabet,
S.K.S.; Luo, C.; Asiedu-Ayeh, E.;
Bamisile, O.; Nyantakyi, I.O.; Adun,
H. A Novel Distributed Media
Caching Technique for Seamless
Video Streaming in Multi-Access
Edge Computing Networks. Appl.
Sci. 2022, 12, 4205. https://doi.org/
10.3390/app12094205
Academic Editor:
Agostino Forestiero
Received: 24 March 2022
Accepted: 20 April 2022
Published: 21 April 2022
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Article
A Novel Distributed Media Caching Technique for Seamless
Video Streaming in Multi-Access Edge Computing Networks
Emmanuel Osei-Mensah
1,
*, Saqr Khalil Saeed Thabet
1
, Chunbo Luo
1,2
, Emelia Asiedu-Ayeh
3
,
Olusola Bamisile
4
, Isaac Osei Nyantakyi
1
and Humphrey Adun
5
1
School of Information and Communication Engineering, University of Electronic Science and Technology
of China, Chengdu 611731, China; saqr-thabet@std.uestc.edu.cn (S.K.S.T.); c.luo@exeter.ac.uk (C.L.);
nyantakyiisaacosei@std.uestc.edu.cn (I.O.N.)
2
Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China,
Huzhou 313001, China
3
School of Management Science and Economics, University of Electronic Science and Technology of China,
Chengdu 611731, China; easieduayeh@std.uestc.edu.cn
4
College of Nuclear Technology and Automation Engineering, Chengdu University of Technology,
Chengdu 610059, China; boomfem@cdut.edu.cn
5
Energy Systems Engineering Department, Faculty of Engineering, Cyprus International University,
Haspolat-Lefkosa, Mersin 10, 99010, Nicosia 99258, Turkey; hadun@ciu.edu.tr
* Correspondence: ecoseimensah@std.uestc.edu.cn
Abstract:
Online video is anticipated to be the largest fraction of all mobile network traffic aside from
the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented
challenges to the current network architecture. Edge caching has been proposed as a highly promising
technology to overcome this challenge by placing computational and data storage resources at the
network edge to reduce latency and backhaul traffic. However, the edge resources are heavily
constrained in their storage and computational capacities as large-scale deployments mean fairly
distributing resources across the network. Addressing this limitation, we propose an edge video
caching scheme that dynamically caches the first part of popularity-ranked video files on Multi-Edge
Computing Access Node (MAN) servers envisioned to achieve higher cache hit ratios, lower latencies,
and lower backhaul traffic. The concept of Regionally Organized Clouds (ROCs) with sufficient
resources for file caching and compute-intensive tasks was introduced, and a formulation of the
edge caching problem as an Integer Linear Programming (ILP) problem was made. Additionally,
this study proposes a file view-time threshold for each cached video aimed at reducing the resource
wastage caused when buffered contents are abandoned. Comparative evaluations of the proposed
show its excellent performance over FIFO, Greedy, LFRU and TLRU schemes.
Keywords:
Multi-Access Edge Computing (MEC); edge caching; distributed computing; resource
allocation; edge network optimization
1. Introduction
Smartphone data traffic is projected to exceed PC data traffic in the next few years
based on the Visual Networking Index by Cisco [
1
]. Internet video traffic accounts for
the highest chunk of all smartphone traffic, reaching about 78 exabytes per month. The
existing cellular networks will be congested; hence, service delivery will be deplorable if
the challenges of video traffic are not addressed. Moreover, the current cloud architecture
provides an inviable solution to the problem, as the number of connected edge-hosted con-
tainers is also estimated to be over 700 million to provide business resilience networking [
2
].
As a result of the heterogeneity of network devices and the dynamics of the network,
video streams must be converted into multiple copies, each with different bitrates, and
stored on main cloud servers. This approach incurs huge operational expenditure, in that it
Appl. Sci. 2022, 12, 4205. https://doi.org/10.3390/app12094205 https://www.mdpi.com/journal/applsci
