In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is...In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is derived in a probabilistic manner.The basic idea can be understood via treating the integrated heterogeneous wireless networks as different coupled and parallel queuing systems.The integrated network performance can approach that of one queue with maximal the multiplexing gain.For the purpose of illustrating the effectively of our proposed model,the Cellular/WLAN interworking is exploited.To minimize the average delay,a heuristic search algorithm is used to get the optimal probability of splitting traffic flow.Further,a Markov process is applied to evaluate the performance of the proposed scheme and compare with that of selecting the best network to access in terms of packet mean delay and blocking probability.Numerical results illustrate our proposed framework is effective and the flow splitting transmission can obtain more performance gain in heterogeneous wireless networks.展开更多
针对现有生成对抗网络的单图像超分辨率重建在大尺度因子下存在训练不稳定、特征提取不足和重建结果纹理细节严重缺失的问题,提出一种拆分注意力网络的单图超分辨率重建方法。首先,以拆分注意力残差模块作为基本残差块构造生成器,提高...针对现有生成对抗网络的单图像超分辨率重建在大尺度因子下存在训练不稳定、特征提取不足和重建结果纹理细节严重缺失的问题,提出一种拆分注意力网络的单图超分辨率重建方法。首先,以拆分注意力残差模块作为基本残差块构造生成器,提高生成器特征提取的能力。其次,在损失函数中引入鲁棒性更好的Charbonnier损失函数和Focal Frequency Loss损失函数代替均方差损失函数,同时加入正则化损失平滑训练结果,防止图像过于像素化。最后,在生成器和判别器中采用谱归一化处理,提高网络的稳定性。在4倍放大因子下,与其他方法在Set5、Set14、BSDS100、Urban100测试集上进行测试比较,本文方法的峰值信噪比比其他对比方法的平均值提升1.419 dB,结构相似性比其他对比方法的平均值提升0.051。实验数据和效果图表明,该方法主观上具有丰富的细节和更好的视觉效果,客观上具有较高的峰值信噪比值和结构相似度值。展开更多
Composite service provision in mobile ad hoc networks encounters great challenges and its success rate is not satisfactory because the nodes' locations are dynamic and the nodes maybe unavailable at any time.Compo...Composite service provision in mobile ad hoc networks encounters great challenges and its success rate is not satisfactory because the nodes' locations are dynamic and the nodes maybe unavailable at any time.Composite service is built through the service composition.In mobile ad hoc networks,the factors influencing the success rate of service composition are mainly the number of nodes and the time spent for the composition.The node's failure probability is proportional to the length of time the node exist in the networks.In order to improve the success rate of service composition,we take several measures.First,we split the service requirement into several segments and cluster the nodes,so that the nodes' waiting time for service composition can be reduced.Second,we propose a new node model of "one node contains multiple services" in mobile ad hoc networks.Using this type of nodes model,the number of nodes required for service composition can be reduced.These means can increase the success rate of service composition.展开更多
Unmanned Aerial Vehicle(UAV)has emerged as a promising technology for the support of human activities,such as target tracking,disaster rescue,and surveillance.However,these tasks require a large computation load of im...Unmanned Aerial Vehicle(UAV)has emerged as a promising technology for the support of human activities,such as target tracking,disaster rescue,and surveillance.However,these tasks require a large computation load of image or video processing,which imposes enormous pressure on the UAV computation platform.To solve this issue,in this work,we propose an intelligent Task Offloading Algorithm(iTOA)for UAV edge computing network.Compared with existing methods,iTOA is able to perceive the network’s environment intelligently to decide the offloading action based on deep Monte Calor Tree Search(MCTS),the core algorithm of Alpha Go.MCTS will simulate the offloading decision trajectories to acquire the best decision by maximizing the reward,such as lowest latency or power consumption.To accelerate the search convergence of MCTS,we also proposed a splitting Deep Neural Network(sDNN)to supply the prior probability for MCTS.The sDNN is trained by a self-supervised learning manager.Here,the training data set is obtained from iTOA itself as its own teacher.Compared with game theory and greedy search-based methods,the proposed iTOA improves service latency performance by 33%and 60%,respectively.展开更多
Software-Defined Network architecture offers network virtualization through a hypervisor plane to share the same physical substrate among multiple virtual networks.However,for this hypervisor plane,how to map a virtua...Software-Defined Network architecture offers network virtualization through a hypervisor plane to share the same physical substrate among multiple virtual networks.However,for this hypervisor plane,how to map a virtual network to the physical substrate while guaranteeing the survivability in the event of failures,is extremely important.In this paper,we present an efficient virtual network mapping approach using optimal backup topology to survive a single link failure with less resource consumption.Firstly,according to whether the path splitting is supported by virtual networks,we propose the OBT-Ⅰ and OBT-Ⅱ algorithms respectively to generate an optimal backup topology which minimizes the total amount of bandwidth constraints.Secondly,we propose a Virtual Network Mapping algorithm with coordinated Primary and Backup Topology(VNM-PBT)to make the best of the substrate network resource.The simulation experiments show that our proposed approach can reduce the average resource consumption and execution time cost,while improving the request acceptance ratio of VNs.展开更多
Many ＂rich - connected＂ topologies with multiple parallel paths between smwers have been proposed for data center networks recently to provide high bisection bandwidth, but it re mains challenging to fully utilize t...Many ＂rich - connected＂ topologies with multiple parallel paths between smwers have been proposed for data center networks recently to provide high bisection bandwidth, but it re mains challenging to fully utilize the high network capacity by appropriate multi- path routing algorithms. As flow-level path splitting may lead to trafl＇ic imbalance between paths due to flow- size difference, packet-level path splitting attracts more attention lately, which spreads packets from flows into multiple available paths and significantly improves link utilizations. However, it may cause packet reordering, confusing the TCP congestion control algorithm and lowering the throughput of flows. In this paper, we design a novel packetlevel multi-path routing scheme called SOPA, which leverag- es OpenFlow to perform packet-level path splitting in a round- robin fashion, and hence significantly mitigates the packet reordering problem and improves the network throughput. Moreover, SOPA leverages the topological feature of data center networks to encode a very small number of switches along the path into the packet header, resulting in very light overhead. Compared with random packet spraying （RPS）, Hedera and equal-cost multi-path routing （ECMP）, our simulations demonstrate that SOPA achieves 29.87%, 50.41% and 77.74% higher network throughput respectively under permutation workload, and reduces average data transfer completion time by 53.65%, 343.31% and 348.25% respectively under production workload.展开更多
基金ACKNOWLEDGEMENT This work was supported by National Natural Science Foundation of China （Grant No. 61231008）, National Basic Research Program of China （973 Program） （Grant No. 2009CB320404）, Program for Changjiang Scholars and Innovative Research Team in University （Grant No. IRT0852）, and the 111 Project （Grant No. B08038）.
文摘In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is derived in a probabilistic manner.The basic idea can be understood via treating the integrated heterogeneous wireless networks as different coupled and parallel queuing systems.The integrated network performance can approach that of one queue with maximal the multiplexing gain.For the purpose of illustrating the effectively of our proposed model,the Cellular/WLAN interworking is exploited.To minimize the average delay,a heuristic search algorithm is used to get the optimal probability of splitting traffic flow.Further,a Markov process is applied to evaluate the performance of the proposed scheme and compare with that of selecting the best network to access in terms of packet mean delay and blocking probability.Numerical results illustrate our proposed framework is effective and the flow splitting transmission can obtain more performance gain in heterogeneous wireless networks.
文摘针对现有生成对抗网络的单图像超分辨率重建在大尺度因子下存在训练不稳定、特征提取不足和重建结果纹理细节严重缺失的问题,提出一种拆分注意力网络的单图超分辨率重建方法。首先,以拆分注意力残差模块作为基本残差块构造生成器,提高生成器特征提取的能力。其次,在损失函数中引入鲁棒性更好的Charbonnier损失函数和Focal Frequency Loss损失函数代替均方差损失函数,同时加入正则化损失平滑训练结果,防止图像过于像素化。最后,在生成器和判别器中采用谱归一化处理,提高网络的稳定性。在4倍放大因子下,与其他方法在Set5、Set14、BSDS100、Urban100测试集上进行测试比较,本文方法的峰值信噪比比其他对比方法的平均值提升1.419 dB,结构相似性比其他对比方法的平均值提升0.051。实验数据和效果图表明,该方法主观上具有丰富的细节和更好的视觉效果,客观上具有较高的峰值信噪比值和结构相似度值。
基金ACKNOWLEDGEMENT This research is supported by the National Grand Fundamental Research 973 Program of China under Grant No. 2011CB302506, 2012CB315802 National Key Technology Research and Development Program of China （Grant No. 2012BAH94F02）+3 种基金 National High-tech R＆D Program of China （863 Program） under Grant No. 2013AA102301 National Natural Science Foundation of China under Grant No. 61132001, 61171102） Program for New Century Excellent Talents in University （Grant No. NCET-11-0592） Project of New Generation Broad band Wireless Networks under Grant No. 2011ZX03002-002-01. The technology development and experiment of innovative networks architecture （CNGI-12- 03-007）.
文摘Composite service provision in mobile ad hoc networks encounters great challenges and its success rate is not satisfactory because the nodes' locations are dynamic and the nodes maybe unavailable at any time.Composite service is built through the service composition.In mobile ad hoc networks,the factors influencing the success rate of service composition are mainly the number of nodes and the time spent for the composition.The node's failure probability is proportional to the length of time the node exist in the networks.In order to improve the success rate of service composition,we take several measures.First,we split the service requirement into several segments and cluster the nodes,so that the nodes' waiting time for service composition can be reduced.Second,we propose a new node model of "one node contains multiple services" in mobile ad hoc networks.Using this type of nodes model,the number of nodes required for service composition can be reduced.These means can increase the success rate of service composition.
基金Supported by the Major Project of National Natural Science Foundation of China （No.20409205） and National High Technology Research and Development Program of China （No.G20070040）.
基金the Artificial Intelligence Key Laboratory of Sichuan Province(Nos.2019RYJ05)National Natural Science Foundation of China(Nos.61971107).
文摘Unmanned Aerial Vehicle(UAV)has emerged as a promising technology for the support of human activities,such as target tracking,disaster rescue,and surveillance.However,these tasks require a large computation load of image or video processing,which imposes enormous pressure on the UAV computation platform.To solve this issue,in this work,we propose an intelligent Task Offloading Algorithm(iTOA)for UAV edge computing network.Compared with existing methods,iTOA is able to perceive the network’s environment intelligently to decide the offloading action based on deep Monte Calor Tree Search(MCTS),the core algorithm of Alpha Go.MCTS will simulate the offloading decision trajectories to acquire the best decision by maximizing the reward,such as lowest latency or power consumption.To accelerate the search convergence of MCTS,we also proposed a splitting Deep Neural Network(sDNN)to supply the prior probability for MCTS.The sDNN is trained by a self-supervised learning manager.Here,the training data set is obtained from iTOA itself as its own teacher.Compared with game theory and greedy search-based methods,the proposed iTOA improves service latency performance by 33%and 60%,respectively.
基金This research was sponsored by the National Basic Research Program （973 program） of China （2012CB315901, 2013C8329104）, the National Natural Science Foundation of China （61372121, 61309020）, and the National High-Tech Research and Development Program （863 Program） of Chi- na （2011AA01A103, 201 1AA01A101, 2013AA013505）.
文摘Software-Defined Network architecture offers network virtualization through a hypervisor plane to share the same physical substrate among multiple virtual networks.However,for this hypervisor plane,how to map a virtual network to the physical substrate while guaranteeing the survivability in the event of failures,is extremely important.In this paper,we present an efficient virtual network mapping approach using optimal backup topology to survive a single link failure with less resource consumption.Firstly,according to whether the path splitting is supported by virtual networks,we propose the OBT-Ⅰ and OBT-Ⅱ algorithms respectively to generate an optimal backup topology which minimizes the total amount of bandwidth constraints.Secondly,we propose a Virtual Network Mapping algorithm with coordinated Primary and Backup Topology(VNM-PBT)to make the best of the substrate network resource.The simulation experiments show that our proposed approach can reduce the average resource consumption and execution time cost,while improving the request acceptance ratio of VNs.
基金supported by the National Basic Research Program of China(973 program)under Grant No.2014CB347800 and No.2012CB315803the National High-Tech R&D Program of China(863 program)under Grant No.2013AA013303+1 种基金the Natural Science Foundation of China under Grant No.61170291,No.61133006,and No.61161140454ZTE IndustryAcademia-Research Cooperation Funds
文摘Many ＂rich - connected＂ topologies with multiple parallel paths between smwers have been proposed for data center networks recently to provide high bisection bandwidth, but it re mains challenging to fully utilize the high network capacity by appropriate multi- path routing algorithms. As flow-level path splitting may lead to trafl＇ic imbalance between paths due to flow- size difference, packet-level path splitting attracts more attention lately, which spreads packets from flows into multiple available paths and significantly improves link utilizations. However, it may cause packet reordering, confusing the TCP congestion control algorithm and lowering the throughput of flows. In this paper, we design a novel packetlevel multi-path routing scheme called SOPA, which leverag- es OpenFlow to perform packet-level path splitting in a round- robin fashion, and hence significantly mitigates the packet reordering problem and improves the network throughput. Moreover, SOPA leverages the topological feature of data center networks to encode a very small number of switches along the path into the packet header, resulting in very light overhead. Compared with random packet spraying （RPS）, Hedera and equal-cost multi-path routing （ECMP）, our simulations demonstrate that SOPA achieves 29.87%, 50.41% and 77.74% higher network throughput respectively under permutation workload, and reduces average data transfer completion time by 53.65%, 343.31% and 348.25% respectively under production workload.
