The traffic within data centers exhibits bursts and unpredictable patterns.This rapid growth in network traffic has two consequences:it surpasses the inherent capacity of the network’s link bandwidth and creates an i...The traffic within data centers exhibits bursts and unpredictable patterns.This rapid growth in network traffic has two consequences:it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load.Consequently,persistent overload situations eventually result in network congestion.The Software Defined Network(SDN)technology is employed in data centers as a network architecture to enhance performance.This paper introduces an adaptive congestion control strategy,named DA-DCTCP,for SDN-based Data Centers.It incorporates Explicit Congestion Notification(ECN)and Round-Trip Time(RTT)to establish congestion awareness and an ECN marking model.To mitigate incorrect congestion caused by abrupt flows,an appropriate ECN marking is selected based on the queue length and its growth slope,and the congestion window(CWND)is adjusted by calculating RTT.Simultaneously,the marking threshold for queue length is continuously adapted using the current queue length of the switch as a parameter to accommodate changes in data centers.The evaluation conducted through Mininet simulations demonstrates that DA-DCTCP yields advantages in terms of throughput,flow completion time(FCT),latency,and resistance against packet loss.These benefits contribute to reducing data center congestion,enhancing the stability of data transmission,and improving throughput.展开更多
The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic ada...The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptationof service requirements and network resources. To address these issues, we propose a multi-constraint pathoptimization scheme based on information fusion in SDN. The proposed scheme collects network topology andnetwork state information on the network side and computes disjoint paths between end hosts. It uses the FuzzyAnalytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters andconstructs a composite quality evaluation function for the paths to determine the priority of the disjoint paths. TheSDN controller extracts the service attributes by analyzing the packet header and selects the optimal path for flowrule forwarding. Furthermore, the service attributes are fed back to the path composite quality evaluation function,and the path priority is dynamically adjusted to achieve dynamic adaptation between service requirements andnetwork status. By continuously monitoring and analyzing the service attributes, the scheme can ensure optimalrouting decisions in response to varying network conditions and evolving service demands. The experimentalresults demonstrated that the proposed scheme can effectively improve average throughput and link utilizationwhile meeting the Quality of Service (QoS) requirements of various applications.展开更多
Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.Howev...Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.展开更多
基金supported by the National Key R&D Program of China(No.2021YFB2700800)the GHfund B(No.202302024490).
文摘The traffic within data centers exhibits bursts and unpredictable patterns.This rapid growth in network traffic has two consequences:it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load.Consequently,persistent overload situations eventually result in network congestion.The Software Defined Network(SDN)technology is employed in data centers as a network architecture to enhance performance.This paper introduces an adaptive congestion control strategy,named DA-DCTCP,for SDN-based Data Centers.It incorporates Explicit Congestion Notification(ECN)and Round-Trip Time(RTT)to establish congestion awareness and an ECN marking model.To mitigate incorrect congestion caused by abrupt flows,an appropriate ECN marking is selected based on the queue length and its growth slope,and the congestion window(CWND)is adjusted by calculating RTT.Simultaneously,the marking threshold for queue length is continuously adapted using the current queue length of the switch as a parameter to accommodate changes in data centers.The evaluation conducted through Mininet simulations demonstrates that DA-DCTCP yields advantages in terms of throughput,flow completion time(FCT),latency,and resistance against packet loss.These benefits contribute to reducing data center congestion,enhancing the stability of data transmission,and improving throughput.
基金the National Key R&D Program of China(No.2021YFB2700800)the GHfund B(No.202302024490).
文摘The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptationof service requirements and network resources. To address these issues, we propose a multi-constraint pathoptimization scheme based on information fusion in SDN. The proposed scheme collects network topology andnetwork state information on the network side and computes disjoint paths between end hosts. It uses the FuzzyAnalytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters andconstructs a composite quality evaluation function for the paths to determine the priority of the disjoint paths. TheSDN controller extracts the service attributes by analyzing the packet header and selects the optimal path for flowrule forwarding. Furthermore, the service attributes are fed back to the path composite quality evaluation function,and the path priority is dynamically adjusted to achieve dynamic adaptation between service requirements andnetwork status. By continuously monitoring and analyzing the service attributes, the scheme can ensure optimalrouting decisions in response to varying network conditions and evolving service demands. The experimentalresults demonstrated that the proposed scheme can effectively improve average throughput and link utilizationwhile meeting the Quality of Service (QoS) requirements of various applications.
基金This present research work was supported by the National Key R&D Program of China(No.2021YFB2700800)the GHfund B(No.202302024490).
文摘Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.
