Network and energy-aware resource selection model for opportunistic grids
Proceedings of the Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE, ISSN: 1524-4547, Page: 167-172
2014
- 3Citations
- 430Usage
- 12Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations3
- Citation Indexes3
- Usage430
- Downloads367
- Abstract Views63
- Captures12
- Readers12
- 12
Conference Paper Description
Due to increasing hardware capacity, computing grids have been handling and processing more data. This has led to higher amount of energy being consumed by grids, hence the necessity for strategies to reduce their energy consumption. Scheduling is a process carried out to define in which node tasks will be executed in the grid. This process can significantly impact the global system performance, including energy consumption. This paper focuses on a scheduling model for opportunistic grids that considers network traffic, distance between input files and execution node as well as the execution node status. The model was tested in a simulated environment created using Green Cloud. The simulation results of this model compared to a usual approach show a total power consumption savings of 7.10%.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84908461549&origin=inward; http://dx.doi.org/10.1109/wetice.2014.31; http://ieeexplore.ieee.org/document/6927044/; http://xplorestaging.ieee.org/ielx7/6909389/6926989/06927044.pdf?arnumber=6927044; https://ir.lib.uwo.ca/electricalpub/45; https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=1092&context=electricalpub
Institute of Electrical and Electronics Engineers (IEEE)
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