Near-Optimal Policies for Energy-Aware Task Assignment in Server Farms

Misikir Eyob Gebrehiwot, Samuli Aalto, Pasi Lassila

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

11 Sitaatiot (Scopus)

Abstrakti

Rising energy costs and the push for green computing have inspired a lot of research effort towards energy efficient computing. Incorporating low energy sleep states in server farms is one of the proposed solutions. This paper studies the trade-off between energy and performance that is inherent in such solutions using the popular cost metric Energy-Response-Time-Weighted-Sum (ERWS). We apply the Markov Decision Process (MDP) theory to the task assignment problem, and derive a near-optimal dynamic task assignment policy for minimizing the ERWS cost metric. Furthermore, we consider a performance constrained energy minimization problem, and provide an algorithm that builds a dynamic task assignment policy by choosing the right energy weight value for the ERWS cost metric. We also show that the resulting task assignment policy behaves like a modified version of the Join the Shortest Queue (JSQ), having a near-optimal performance by minimizing energy consumption while still obeying response time constraint.

AlkuperäiskieliEnglanti
OtsikkoProceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017
KustantajaIEEE
Sivut1017-1026
Sivumäärä10
ISBN (elektroninen)9781509066100
DOI - pysyväislinkit
TilaJulkaistu - 10 heinäk. 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE/ACM International Symposium on Cluster, Cloud and Grid Computing - Madrid, Espanja
Kesto: 14 toukok. 201717 toukok. 2017
Konferenssinumero: 17

Julkaisusarja

NimiIEEE-ACM International Symposium on Cluster Cloud and Grid Computing
ISSN (painettu)2376-4414

Conference

ConferenceIEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
LyhennettäCCGRID
Maa/AlueEspanja
KaupunkiMadrid
Ajanjakso14/05/201717/05/2017

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