AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers

Edge data centers are increasingly deployed to improve response time of intelligent services. Due to the high computing demands for such services, edge data centers consume a considerable amount of power, generating excessive heat. To mitigate thermal problems with a smaller cooling power, edge data...

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Main Authors: Seung Hun Choi, Seon Young Kim, Young Geun Kim, Joonho Kong, Sung Woo Chung
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10173485/
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author Seung Hun Choi
Seon Young Kim
Young Geun Kim
Joonho Kong
Sung Woo Chung
author_facet Seung Hun Choi
Seon Young Kim
Young Geun Kim
Joonho Kong
Sung Woo Chung
author_sort Seung Hun Choi
collection DOAJ
description Edge data centers are increasingly deployed to improve response time of intelligent services. Due to the high computing demands for such services, edge data centers consume a considerable amount of power, generating excessive heat. To mitigate thermal problems with a smaller cooling power, edge data centers usually trigger software-based thermal management techniques along with the air cooling systems. Unfortunately, the ambient temperature of servers often has a surge due to the consolidation of VMs and heat propagation among components (e.g., CPU, GPU, memory unit, disk, etc.). Higher ambient temperature further increases the on-chip temperature, invoking more frequent thermal throttling. To resolve thermal problems deteriorated by the ambient temperature, in this paper, we propose an ambient temperature aware VM allocation technique, called AMBITION. Considering the performance impact of ambient temperature, AMBITION estimates the actual computing capacity of servers. Based on the computing demands of VMs, AMBITION finds an appropriate server which has sufficient ambient-aware computing capacity to run the VM; it allocates computation-intensive VMs to the servers with the higher ambient-aware computing capacity, and distributes memory-intensive VMs to the individual servers as much as possible. In our experiments on an edge data center, AMBITION shows the execution time speedup of 50.3%, on average (up to 73.8%), compared to a conventional VM allocation technique while saving system-wide energy by 5.9% (up to 13.6%). At the expense of 5.8% speedup (from 50.3% to 44.5%), AMBITION further saves cooling power by 84.3%, leading to 29.3% of total edge data center energy saving.
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spelling doaj.art-1cd5e6cef26a4d6783cc49aa9797594f2023-07-13T23:00:49ZengIEEEIEEE Access2169-35362023-01-0111685016851110.1109/ACCESS.2023.329234210173485AMBITION: Ambient Temperature Aware VM Allocation for Edge Data CentersSeung Hun Choi0Seon Young Kim1Young Geun Kim2https://orcid.org/0000-0003-4713-819XJoonho Kong3https://orcid.org/0000-0002-9013-9561Sung Woo Chung4https://orcid.org/0000-0001-5347-9586Department of Computer Science and Engineering, Korea University, Seoul, Republic of KoreaElectronics and Telecommunications Research Institute, Daejeon, Republic of KoreaDepartment of Computer Science and Engineering, Korea University, Seoul, Republic of KoreaSchool of Electronics Engineering, Kyungpook National University, Daegu, Republic of KoreaDepartment of Computer Science and Engineering, Korea University, Seoul, Republic of KoreaEdge data centers are increasingly deployed to improve response time of intelligent services. Due to the high computing demands for such services, edge data centers consume a considerable amount of power, generating excessive heat. To mitigate thermal problems with a smaller cooling power, edge data centers usually trigger software-based thermal management techniques along with the air cooling systems. Unfortunately, the ambient temperature of servers often has a surge due to the consolidation of VMs and heat propagation among components (e.g., CPU, GPU, memory unit, disk, etc.). Higher ambient temperature further increases the on-chip temperature, invoking more frequent thermal throttling. To resolve thermal problems deteriorated by the ambient temperature, in this paper, we propose an ambient temperature aware VM allocation technique, called AMBITION. Considering the performance impact of ambient temperature, AMBITION estimates the actual computing capacity of servers. Based on the computing demands of VMs, AMBITION finds an appropriate server which has sufficient ambient-aware computing capacity to run the VM; it allocates computation-intensive VMs to the servers with the higher ambient-aware computing capacity, and distributes memory-intensive VMs to the individual servers as much as possible. In our experiments on an edge data center, AMBITION shows the execution time speedup of 50.3%, on average (up to 73.8%), compared to a conventional VM allocation technique while saving system-wide energy by 5.9% (up to 13.6%). At the expense of 5.8% speedup (from 50.3% to 44.5%), AMBITION further saves cooling power by 84.3%, leading to 29.3% of total edge data center energy saving.https://ieeexplore.ieee.org/document/10173485/Ambient temperaturecomputing capacityedge data centersheterogeneous serversVM allocation
spellingShingle Seung Hun Choi
Seon Young Kim
Young Geun Kim
Joonho Kong
Sung Woo Chung
AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers
IEEE Access
Ambient temperature
computing capacity
edge data centers
heterogeneous servers
VM allocation
title AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers
title_full AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers
title_fullStr AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers
title_full_unstemmed AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers
title_short AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers
title_sort ambition ambient temperature aware vm allocation for edge data centers
topic Ambient temperature
computing capacity
edge data centers
heterogeneous servers
VM allocation
url https://ieeexplore.ieee.org/document/10173485/
work_keys_str_mv AT seunghunchoi ambitionambienttemperatureawarevmallocationforedgedatacenters
AT seonyoungkim ambitionambienttemperatureawarevmallocationforedgedatacenters
AT younggeunkim ambitionambienttemperatureawarevmallocationforedgedatacenters
AT joonhokong ambitionambienttemperatureawarevmallocationforedgedatacenters
AT sungwoochung ambitionambienttemperatureawarevmallocationforedgedatacenters