TY - GEN
T1 - Budget-constrained bulk data transfer via internet and shipping networks
AU - Cho, Brian
AU - Gupta, Indranil
PY - 2011
Y1 - 2011
N2 - Cloud collaborators wish to combine large amounts of data, in the order of TBs, from multiple distributed locations to a single datacenter. Such groups are faced with the challenge of reducing the latency of the transfer, without incurring excessive dollar costs. Our Pandora system is an autonomic system that creates data transfer plans that can satisfy latency and cost needs, by considering transferring the data through both Internet and disk shipments. Solving the planning problem is a critical step towards a truly autonomic bulk data transfer service. In this paper, we develop techniques to create an optimal transfer plan that minimizes transfer latency subject to a budget constraint. To systematically explore the solution space, we develop efficient binary search methods that find the optimal shipment transfer plan. Our experimental evaluation, driven by Internet bandwidth traces and actual shipment costs queried from FedEx web services, shows that these techniques work well on diverse, realistic networks.
AB - Cloud collaborators wish to combine large amounts of data, in the order of TBs, from multiple distributed locations to a single datacenter. Such groups are faced with the challenge of reducing the latency of the transfer, without incurring excessive dollar costs. Our Pandora system is an autonomic system that creates data transfer plans that can satisfy latency and cost needs, by considering transferring the data through both Internet and disk shipments. Solving the planning problem is a critical step towards a truly autonomic bulk data transfer service. In this paper, we develop techniques to create an optimal transfer plan that minimizes transfer latency subject to a budget constraint. To systematically explore the solution space, we develop efficient binary search methods that find the optimal shipment transfer plan. Our experimental evaluation, driven by Internet bandwidth traces and actual shipment costs queried from FedEx web services, shows that these techniques work well on diverse, realistic networks.
KW - cloud computing
KW - data-intensive computing
KW - wide-area data transfer
UR - http://www.scopus.com/inward/record.url?scp=79960152104&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960152104&partnerID=8YFLogxK
U2 - 10.1145/1998582.1998595
DO - 10.1145/1998582.1998595
M3 - Conference contribution
AN - SCOPUS:79960152104
SN - 9781450306072
T3 - Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
SP - 71
EP - 80
BT - Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
T2 - 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
Y2 - 14 June 2011 through 18 June 2011
ER -