With the multi-tier pricing scheme provided by most of the cloud service providers （CSPs）, the cloud userstypically select a high enough transmission service level to ensure the quality of service （QoS）, due to th...With the multi-tier pricing scheme provided by most of the cloud service providers （CSPs）, the cloud userstypically select a high enough transmission service level to ensure the quality of service （QoS）, due to the severe penalty ofmissing the transmission deadline. This leads to the so-called over-provisioning problem, which increases the transmissioncost of the cloud user. Given the fact that cloud users may not be aware of their traffic demand before accessing the network,the over-provisioning problem becomes more serious. In this paper, we investigate how to reduce the transmission cost fromthe perspective of cloud users, especially when they are not aware of their traffic demand before the transmission deadline.The key idea is to split a long-term transmission request into several short ones. By selecting the most suitable transmissionservice level for each short-term request, a cost-efiqcient inter-datacenter transmission service level selection framework isobtained. We further formulate the transmission service level selection problem as a linear programming problem andresolve it in an on-line style with Lyapunov optimization. We evaluate the proposed approach with real traffic data. Theexperimental results show that our method can reduce the transmission cost by up to 65.04%.展开更多
基金This work is partially supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000205, the State Key Program of National Natural Science Foundation of China under Grant No. 61432002, the National Natural Science Foundation of China-Guangdong Joint Fund under Grant No. U1701263, the National Natural Science Foundation of China under Grant Nos. 61702365, 61672379, and 61772112, the Natural Science Foundation of Tianjin under Grant Nos. 17JCQNJC00700 and 17JCYBJC15500, and the Special Program of Artificial Intelligence of Tianjin Municipal Science and Technology Commission under Grant No. 17ZXRGGX00150.
文摘With the multi-tier pricing scheme provided by most of the cloud service providers （CSPs）, the cloud userstypically select a high enough transmission service level to ensure the quality of service （QoS）, due to the severe penalty ofmissing the transmission deadline. This leads to the so-called over-provisioning problem, which increases the transmissioncost of the cloud user. Given the fact that cloud users may not be aware of their traffic demand before accessing the network,the over-provisioning problem becomes more serious. In this paper, we investigate how to reduce the transmission cost fromthe perspective of cloud users, especially when they are not aware of their traffic demand before the transmission deadline.The key idea is to split a long-term transmission request into several short ones. By selecting the most suitable transmissionservice level for each short-term request, a cost-efiqcient inter-datacenter transmission service level selection framework isobtained. We further formulate the transmission service level selection problem as a linear programming problem andresolve it in an on-line style with Lyapunov optimization. We evaluate the proposed approach with real traffic data. Theexperimental results show that our method can reduce the transmission cost by up to 65.04%.
