Software-Defined Networking(SDN)adapts logically-centralized control by decoupling control plane from data plane and provides the efficient use of network resources.However,due to the limitation of traditional routing...Software-Defined Networking(SDN)adapts logically-centralized control by decoupling control plane from data plane and provides the efficient use of network resources.However,due to the limitation of traditional routing strategies relying on manual configuration,SDN may suffer from link congestion and inefficient bandwidth allocation among flows,which could degrade network performance significantly.In this paper,we propose EARS,an intelligence-driven experiential network architecture for automatic routing.EARS adapts deep reinforcement learning(DRL)to simulate the human methods of learning experiential knowledge,employs the closed-loop network control mechanism incorporating with network monitoring technologies to realize the interaction with network environment.The proposed EARS can learn to make better control decision from its own experience by interacting with network environment and optimize the network intelligently by adjusting services and resources offered based on network requirements and environmental conditions.Under the network architecture,we design the network utility function with throughput and delay awareness,differentiate flows based on their size characteristics,and design a DDPGbased automatic routing algorithm as DRL decision brain to find the near-optimal paths for mice and elephant flows.To validate the network architecture,we implement it on a real network environment.Extensive simulation results show that EARS significantly improve the network throughput and reduces the average packet delay in comparison with baseline schemes(e.g.OSPF,ECMP).展开更多
Automatic placement and routing technology provides an effective tool for designing simulation and information guidance.Various intelligent algorithms in mechanical design,ocean and ship engineering and aerospace desi...Automatic placement and routing technology provides an effective tool for designing simulation and information guidance.Various intelligent algorithms in mechanical design,ocean and ship engineering and aerospace design have been implemented.However,automatic placement and routing has never been integrated into interactive 3D application.In this paper,idea of combining the interactive 3D application with automatic placement and routing is proposed,and its main issue is discussed.Then we present a new placement and routing algorithm suitable for 3D interactive application containing model design,fundamental algorithm and global optimization to remove routing blockage.Experimental results demonstrate that the proposed algorithm works effectively in simulation,meets the requirements of real-time rendering and has great practical value.展开更多
基金supported by the National Natural Science Foundation of China for Innovative Research Groups (61521003)the National Natural Science Foundation of China (61872382)+1 种基金the National Key Research and Development Program of China (2017YFB0803204)the Research and Development Program in Key Areas of Guangdong Province (No.2018B010113001)
文摘Software-Defined Networking(SDN)adapts logically-centralized control by decoupling control plane from data plane and provides the efficient use of network resources.However,due to the limitation of traditional routing strategies relying on manual configuration,SDN may suffer from link congestion and inefficient bandwidth allocation among flows,which could degrade network performance significantly.In this paper,we propose EARS,an intelligence-driven experiential network architecture for automatic routing.EARS adapts deep reinforcement learning(DRL)to simulate the human methods of learning experiential knowledge,employs the closed-loop network control mechanism incorporating with network monitoring technologies to realize the interaction with network environment.The proposed EARS can learn to make better control decision from its own experience by interacting with network environment and optimize the network intelligently by adjusting services and resources offered based on network requirements and environmental conditions.Under the network architecture,we design the network utility function with throughput and delay awareness,differentiate flows based on their size characteristics,and design a DDPGbased automatic routing algorithm as DRL decision brain to find the near-optimal paths for mice and elephant flows.To validate the network architecture,we implement it on a real network environment.Extensive simulation results show that EARS significantly improve the network throughput and reduces the average packet delay in comparison with baseline schemes(e.g.OSPF,ECMP).
基金supported by the National High-Technology Research and Development Program of China (Grant No.2007AA01Z319)the National Natural Science Foundation of China (Grant No.60873130)the Key Discipline Development Program of Shanghai Municipal Education Commission (Grant No.J50104)
文摘Automatic placement and routing technology provides an effective tool for designing simulation and information guidance.Various intelligent algorithms in mechanical design,ocean and ship engineering and aerospace design have been implemented.However,automatic placement and routing has never been integrated into interactive 3D application.In this paper,idea of combining the interactive 3D application with automatic placement and routing is proposed,and its main issue is discussed.Then we present a new placement and routing algorithm suitable for 3D interactive application containing model design,fundamental algorithm and global optimization to remove routing blockage.Experimental results demonstrate that the proposed algorithm works effectively in simulation,meets the requirements of real-time rendering and has great practical value.