Open AccessMice flow aggregation approach for Green networking
Author(s) -
Lin QinLiang,
Yu ShunZheng
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5466
Subject(s) - sleep mode , computer science , flow (mathematics) , scheduling (production processes) , set (abstract data type) , flow network , energy (signal processing) , computer network , mathematics , physics , mathematical optimization , mechanics , power (physics) , statistics , power consumption , quantum mechanics , programming language
Studies have shown that most of the flows in data centres are mice flows and last short time. However, existing green networking solutions do not consider this traffic characteristic. A mass of mice flows may be rerouted after network equipment is put into sleep mode and this can result in significant degradation of network performance. In this study, the authors propose a novel solution for green networking called energy‐efficient flow scheduling approach (EFSA). EFSA aggregates mice flow into a minimal set of links, and the largest flows that result in an overload of links in the set are rerouted in time. Instead of managing every mice flows, only a few numbers of largest flows are rerouted. Unused switches/links will be put into sleep mode for energy saving. The evaluation of EFSA shows that it can significantly reduce the number of rerouted flows and improve the performance of data centre networks while saving network energy efficiently.