TY - GEN
T1 - Intelligent Bandwidth Reservation for Big Data Transfer in High-Performance Networks
AU - Zuo, Liudong
AU - Zhu, Michelle M.
AU - Wu, Chase Q.
AU - Hou, Aiqin
N1 - Funding Information: It is of our future interest to integrate the proposed algorithms in real-life HPNs and deepen our research on bandwidth scheduling for BRRs with different priorities. ACKNOWLEDGMENT This research is sponsored partially by the Ministry of Science and Technology of China under Grant No. 2017YFB1300301 and National Nature Science Foundation of China under Grant No. 61472320 and U1609202 with Northwest University, P.R. China. REFERENCES
PY - 2018/7/27
Y1 - 2018/7/27
N2 - Many scientific applications are generating extremely large amounts of data at a high speed, which must be transferred to remote collaborating sites for storage and analysis. Such high- demanding data transfer has been increasingly supported by bandwidth reservation services in high-performance networks (HPNs). For each bandwidth reservation request (BRR), most existing scheduling algorithms return either the best-case reservation option or a reject message if the BRR cannot be satisfied. To perform intelligent scheduling, we provide two alternative reservation options in the latter case: schedule the BRR within the closest time intervals before and after the user-specified time interval. We consider two different types of BRRs and for each, we design a flexible bandwidth scheduling algorithm with a rigorous optimality proof to compute both the best and alternative reservation options. For comparison, we also design two heuristics adapted from existing bandwidth scheduling algorithms. Extensive simulations show that the proposed algorithms have superior performance to those in comparison.
AB - Many scientific applications are generating extremely large amounts of data at a high speed, which must be transferred to remote collaborating sites for storage and analysis. Such high- demanding data transfer has been increasingly supported by bandwidth reservation services in high-performance networks (HPNs). For each bandwidth reservation request (BRR), most existing scheduling algorithms return either the best-case reservation option or a reject message if the BRR cannot be satisfied. To perform intelligent scheduling, we provide two alternative reservation options in the latter case: schedule the BRR within the closest time intervals before and after the user-specified time interval. We consider two different types of BRRs and for each, we design a flexible bandwidth scheduling algorithm with a rigorous optimality proof to compute both the best and alternative reservation options. For comparison, we also design two heuristics adapted from existing bandwidth scheduling algorithms. Extensive simulations show that the proposed algorithms have superior performance to those in comparison.
KW - Bandwidth reservation
KW - Dynamic provisioning
KW - High-performance networks
KW - Quality of Service
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U2 - https://doi.org/10.1109/ICC.2018.8422601
DO - https://doi.org/10.1109/ICC.2018.8422601
M3 - Conference contribution
SN - 9781538631805
VL - 2018-May
T3 - 2018-May
BT - 2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 20 May 2018 through 24 May 2018
ER -