Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue wit...Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.展开更多
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...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supported by a grant from the National Basic Research Development Program of China(973 Program)(No.2012CB315901,2012CB315906)the National High Technology Research and Development Program of China(863 Program)(No.2011AA01A103)
文摘Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.
基金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%.
