Abstract
Many next-generation e-science applications require fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliability requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.
| Original language | English |
|---|---|
| Pages (from-to) | 1-16 |
| Number of pages | 16 |
| Journal | Computer Networks |
| Volume | 113 |
| DOIs | |
| State | Published - 11 Feb 2017 |
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Keywords
- Bandwidth reservation
- Bandwidth scheduling
- Dynamic provisioning
- Fault tolerance
- High-performance networks
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Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks. / Zuo, Liudong; Zhu, Michelle M.; Wu, Chase Q.; Zurawski, Jason.
In: Computer Networks, Vol. 113, 11.02.2017, p. 1-16.Research output: Contribution to journal › Article
TY - JOUR
T1 - Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks
AU - Zuo, Liudong
AU - Zhu, Michelle M.
AU - Wu, Chase Q.
AU - Zurawski, Jason
PY - 2017/2/11
Y1 - 2017/2/11
N2 - Many next-generation e-science applications require fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliability requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.
AB - Many next-generation e-science applications require fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliability requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.
KW - Bandwidth reservation
KW - Bandwidth scheduling
KW - Dynamic provisioning
KW - Fault tolerance
KW - High-performance networks
UR - http://www.scopus.com/inward/record.url?scp=85000893445&partnerID=8YFLogxK
U2 - 10.1016/j.comnet.2016.11.003
DO - 10.1016/j.comnet.2016.11.003
M3 - Article
AN - SCOPUS:85000893445
VL - 113
SP - 1
EP - 16
JO - Computer Networks
JF - Computer Networks
SN - 1389-1286
ER -