GreenPar-Reference-Cited by-同舟云学术

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GreenPar

Published:2015-06-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM on International Conference on Supercomputing
language:
Short-container-title:

Author:

Haque Md E.¹,Goiri Iigo²,Bianchini Ricardo³,Nguyen Thu D.¹

Affiliation:

1. Rutgers University, Piscataway, NJ, USA

2. Microsoft Research, Redmond, WA, USA

3. Rutgers University, Piscataway, NJ & Microsoft Research, Redmond, WA, USA

Funder

National Science Foundation

Rutgers University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2751205.2751221

Reference42 articles.

1. Utilizing green energy prediction to schedule mixed batch and service jobs in data centers

2. Energy-Efficient Algorithms for Flow Time Minimization

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CloudSimPer: Simulating Geo-Distributed Datacenters Powered by Renewable Energy Mix;IEEE Transactions on Parallel and Distributed Systems;2024-04

2. Versatility or validity: A comprehensive review on simulation of Datacenters powered by Renewable Energy mix;Future Generation Computer Systems;2022-11

3. Harnessing Task Usage Prediction and Latency Sensitivity for Scheduling Workloads in Wind-Powered Data Centers;Energies;2022-06-19

4. GreenPacker: renewable- and fragmentation-aware VM placement for geographically distributed green data centers;The Journal of Supercomputing;2021-06-09

5. Scheduling Challenges for Variable Capacity Resources;Job Scheduling Strategies for Parallel Processing;2021

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