TY - GEN
T1 - Traffic regulation under the percentile-based pricing policy
AU - Wang, Jianping
PY - 2006
Y1 - 2006
N2 - With the emerging concept of utility computing, appropriate business models are becoming more and more important for the Internet services. Internet Service Providers (ISP) measure IP network usage for billing in different ways. Percentile-based pricing policy is one of the common billing methods. Percentile-based measurement allows the ISP to bill the customer for the maximum bandwidth used during the billing period while forgiving a small amount of bandwidth spiking. In this paper, we investigate how a customer can regulate the traffic volume under the constraint of a predetermined budget such that the amount of band-width spiking is within the range that the ISP can tolerate. Optimal solutions are presented for the offline case where the traffic demands in each small period are given. A traffic scheduling algorithm is given for the online case where the traffic demands in each small period are unknown in advance. Computations are conducted to illustrate the effectiveness of our solutions. © 2006 ACM.
AB - With the emerging concept of utility computing, appropriate business models are becoming more and more important for the Internet services. Internet Service Providers (ISP) measure IP network usage for billing in different ways. Percentile-based pricing policy is one of the common billing methods. Percentile-based measurement allows the ISP to bill the customer for the maximum bandwidth used during the billing period while forgiving a small amount of bandwidth spiking. In this paper, we investigate how a customer can regulate the traffic volume under the constraint of a predetermined budget such that the amount of band-width spiking is within the range that the ISP can tolerate. Optimal solutions are presented for the offline case where the traffic demands in each small period are given. A traffic scheduling algorithm is given for the online case where the traffic demands in each small period are unknown in advance. Computations are conducted to illustrate the effectiveness of our solutions. © 2006 ACM.
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U2 - 10.1145/1146847.1146851
DO - 10.1145/1146847.1146851
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 1595934286
SN - 9781595934284
VL - 152
BT - ACM International Conference Proceeding Series
T2 - 1st International Conference on Scalable Information Systems, InfoScale '06
Y2 - 30 May 2006 through 1 June 2006
ER -