The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

Throughput-Conscious Energy Allocation and Reliability-Aware Task Assignment for Renewable Powered In-Situ Server Systems

Throughput-Conscious Energy Allocation and Reliability-Aware Task Assignment for Renewable Powered In-Situ Server Systems
Throughput-Conscious Energy Allocation and Reliability-Aware Task Assignment for Renewable Powered In-Situ Server Systems

In-situ (InS) server systems are typically deployed in special environments to handle in-situ workloads which are generated from environmentally sensitive areas or remote places lacking modern power supply infrastructure. This special operating environment of InS servers urges such systems to be powered by renewable energy. In addition, the InS systems are vulnerable to soft errors due to the harsh environments they deploy. This paper tackles the problem of allocating harvested energy to renewable powered servers and assigning the in-situ workloads to these servers for optimizing throughput of both the overall system and individual servers under energy and reliability constraints. We perform the energy allocation based on system state. In particular, for systems in low energy state, we propose a game theoretic approach that models the energy allocation as a cooperative game among multiple servers and derives a Nash bargaining solution. To meet the reliability constraint, we analyze the reliability optimality of assigning tasks to multiple servers and design a reliability-aware task assignment heuristic based on the analysis. Experimental results show that with a small time overhead, the proposed energy allocation approach achieves a high throughput from perspectives of both the overall system and individual servers, and the proposed task assignment approach ensures an increased system reliability.

Energy states, Reliability, Renewable energy, Renewable energy sources, Resource management, Servers, Task analysis, Throughput, energy allocation, game theory., in-situ server, reliability, task assignment, throughput
0278-0070
Zhou, Junlong
a1547c86-99bb-4810-8275-96db0e4b6048
Cao, Kun
7c86cb0c-4741-4c11-a93f-eb1db2fae1b8
Zhou, Xiumin
469c78ae-2b7c-4c65-bf32-d439229f5298
Chen, Mingsong
ffb373e5-be69-4824-a6c1-4eafc175aecb
Wei, Tongquan
482d149e-149f-4104-899d-a23e25d5e7e1
Hu, Shiyan
19bb09b2-bf52-4bd7-818a-63e8da474072
Zhou, Junlong
a1547c86-99bb-4810-8275-96db0e4b6048
Cao, Kun
7c86cb0c-4741-4c11-a93f-eb1db2fae1b8
Zhou, Xiumin
469c78ae-2b7c-4c65-bf32-d439229f5298
Chen, Mingsong
ffb373e5-be69-4824-a6c1-4eafc175aecb
Wei, Tongquan
482d149e-149f-4104-899d-a23e25d5e7e1
Hu, Shiyan
19bb09b2-bf52-4bd7-818a-63e8da474072

Zhou, Junlong, Cao, Kun, Zhou, Xiumin, Chen, Mingsong, Wei, Tongquan and Hu, Shiyan (2021) Throughput-Conscious Energy Allocation and Reliability-Aware Task Assignment for Renewable Powered In-Situ Server Systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. (doi:10.1109/TCAD.2021.3068095).

Record type: Article

Abstract

In-situ (InS) server systems are typically deployed in special environments to handle in-situ workloads which are generated from environmentally sensitive areas or remote places lacking modern power supply infrastructure. This special operating environment of InS servers urges such systems to be powered by renewable energy. In addition, the InS systems are vulnerable to soft errors due to the harsh environments they deploy. This paper tackles the problem of allocating harvested energy to renewable powered servers and assigning the in-situ workloads to these servers for optimizing throughput of both the overall system and individual servers under energy and reliability constraints. We perform the energy allocation based on system state. In particular, for systems in low energy state, we propose a game theoretic approach that models the energy allocation as a cooperative game among multiple servers and derives a Nash bargaining solution. To meet the reliability constraint, we analyze the reliability optimality of assigning tasks to multiple servers and design a reliability-aware task assignment heuristic based on the analysis. Experimental results show that with a small time overhead, the proposed energy allocation approach achieves a high throughput from perspectives of both the overall system and individual servers, and the proposed task assignment approach ensures an increased system reliability.

This record has no associated files available for download.

More information

Accepted/In Press date: 2021
e-pub ahead of print date: 23 March 2021
Additional Information: Publisher Copyright: IEEE Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: Energy states, Reliability, Renewable energy, Renewable energy sources, Resource management, Servers, Task analysis, Throughput, energy allocation, game theory., in-situ server, reliability, task assignment, throughput

Identifiers

Local EPrints ID: 449944
URI: http://eprints.soton.ac.uk/id/eprint/449944
ISSN: 0278-0070
PURE UUID: 07045500-d573-4dfa-b6f6-c0830ee7fa78

Catalogue record

Date deposited: 28 Jun 2021 16:32
Last modified: 28 Jun 2021 16:32

Export record

Altmetrics

Contributors

Author: Junlong Zhou
Author: Kun Cao
Author: Xiumin Zhou
Author: Mingsong Chen
Author: Tongquan Wei
Author: Shiyan Hu

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×