TY - GEN
T1 - Towards Optimal System Deployment for Edge Computing
T2 - 29th International Conference on Computer Communications and Networks, ICCCN 2020
AU - Li, Dawei
AU - Asikaburu, Chigozie
AU - Dong, Boxiang
AU - Zhou, Huan
AU - Azizi, Sadoon
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/8
Y1 - 2020/8
N2 - In this preliminary study, we consider the server allocation problem for edge computing system deployment. Our goal is to minimize the average turnaround time of application requests/tasks, generated by all mobile devices/users in a geographical region. We consider two approaches for edge cloud deployment: the flat deployment, where all edge clouds co-locate with the base stations, and the hierarchical deployment, where edge clouds can also co-locate with other system components besides the base stations. In the flat deployment, we demonstrate that the allocation of edge cloud servers should be balanced across all the base stations, if the application request arrival rates at the base stations are equal to each other. We also show that the hierarchical deployment approach has great potentials in minimizing the system's average turnaround time. We conduct various simulation studies using the CloudSim Plus platform to verify our theoretical results. The collective findings trough theoretical analysis and simulation results will provide useful guidance in practical edge computing system deployment.
AB - In this preliminary study, we consider the server allocation problem for edge computing system deployment. Our goal is to minimize the average turnaround time of application requests/tasks, generated by all mobile devices/users in a geographical region. We consider two approaches for edge cloud deployment: the flat deployment, where all edge clouds co-locate with the base stations, and the hierarchical deployment, where edge clouds can also co-locate with other system components besides the base stations. In the flat deployment, we demonstrate that the allocation of edge cloud servers should be balanced across all the base stations, if the application request arrival rates at the base stations are equal to each other. We also show that the hierarchical deployment approach has great potentials in minimizing the system's average turnaround time. We conduct various simulation studies using the CloudSim Plus platform to verify our theoretical results. The collective findings trough theoretical analysis and simulation results will provide useful guidance in practical edge computing system deployment.
KW - CloudSim Plus
KW - Edge computing
KW - average turnaround time
KW - edge cloud
KW - flat deployment
KW - hierarchical deployment
UR - http://www.scopus.com/inward/record.url?scp=85093855240&partnerID=8YFLogxK
U2 - 10.1109/ICCCN49398.2020.9209754
DO - 10.1109/ICCCN49398.2020.9209754
M3 - Conference contribution
AN - SCOPUS:85093855240
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - ICCCN 2020 - 29th International Conference on Computer Communications and Networks
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 August 2020 through 6 August 2020
ER -