The paper proposes a decentralized concurrent transmission strategy in shared channels based on an incomplete information game in Ad Hoc networks.Based on the nodal channel quality,the game can work out a channel gain...The paper proposes a decentralized concurrent transmission strategy in shared channels based on an incomplete information game in Ad Hoc networks.Based on the nodal channel quality,the game can work out a channel gain threshold,which decides the candidates for taking part in the concurrent transmission.The utility formula is made for maximizing the overall throughput based on channel quality variation.For an achievable Bayesian Nash equilibrium（BNE） solution,this paper further prices the selfish players in utility functions for attempting to improve the channel gain one-sidedly.Accordingly,this game allows each node to distributedly decide whether to transmit concurrently with others depending on the Nash equilibrium（NE）.Besides,to make the proposed game practical,this paper next presents an efficient particle swarm optimization（PSO） model to fasten the otherwise very slow convergence procedure due to the large computational complexity.Numerical results show the proposed approach is feasible to increase concurrent transmission opportunities for active nodes and the convergence can be swiftly obtained with a few of iteration times by the proposed PSO algorithm.展开更多
With the increasing demand for marine exploration, underwater acoustic sensor networks (UASNs) are prone to have the characteristics of large-scale, long term monitoring, and high data traffic load. Underwater media a...With the increasing demand for marine exploration, underwater acoustic sensor networks (UASNs) are prone to have the characteristics of large-scale, long term monitoring, and high data traffic load. Underwater media access control (MAC) protocols, which allow multiple users to share the common medium fairly and efficiently, are essential for the performance of UASNs. However, the design of MAC protocols is confronted with the challenges of spatial unfairness, data eruption, and low energy efficiency. In this paper, we propose a novel data concurrent transmission (DCT) MAC protocol, which is able to exploit long propagation delay and conduct concurrent transmission. Specifically, we present the theoretical performance analysis of the proposed MAC protocol in detail and give an analytical solution of the success concurrent transmission probability between nodes. In addition, simulation results are provided to demonstrate that our proposed protocol is appropriate for UASNs and can significantly improve the performance in terms of network throughput and energy consumption. Finally, we give some typical future applications of UASNs and discuss the demands on MAC protocol design.展开更多
The communication in the Millimeter-wave(mmWave)band,i.e.,30~300 GHz,is characterized by short-range transmissions and the use of antenna beamforming(BF).Thus,multiple mmWave access points(APs)should be installed to f...The communication in the Millimeter-wave(mmWave)band,i.e.,30~300 GHz,is characterized by short-range transmissions and the use of antenna beamforming(BF).Thus,multiple mmWave access points(APs)should be installed to fully cover a target environment with gigabits per second(Gbps)connectivity.However,inter-beam interference prevents maximizing the sum rates of the established concurrent links.In this paper,a reinforcement learning(RL)approach is proposed for enabling mmWave concurrent transmissions by finding out beam directions that maximize the long-term average sum rates of the concurrent links.Specifically,the problem is formulated as a multiplayer multiarmed bandit(MAB),where mmWave APs act as the players aiming to maximize their achievable rewards,i.e.,data rates,and the arms to play are the available beam directions.In this setup,a selfish concurrent multiplayer MAB strategy is advocated.Four different MAB algorithms,namely,ϵ-greedy,upper confidence bound(UCB),Thompson sampling(TS),and exponential weight algorithm for exploration and exploitation(EXP3)are examined by employing them in each AP to selfishly enhance its beam selection based only on its previous observations.After a few rounds of interactions,mmWave APs learn how to select concurrent beams that enhance the overall system performance.The proposed MAB based mmWave concurrent BF shows comparable performance to the optimal solution.展开更多
Concurrent multipath transfer（CMT） using stream control transmission protocol（SCTP） multihoming has become an appealing option to increase the throughput and improve the performance of increasingly bandwidth-hungr...Concurrent multipath transfer（CMT） using stream control transmission protocol（SCTP） multihoming has become an appealing option to increase the throughput and improve the performance of increasingly bandwidth-hungry applications.To investigate the rate allocation for applications in CMT,this paper analyzes the capacities of paths shared by competing sources,then proposes the rate allocation model for elastic flows based on the framework of network utility maximization（NUM）.In order to obtain the global optimum of the model,a distributed algorithm is presented which depends only on local available information.Simulation results confirm that the proposed algorithm can achieve the global optimum within reasonable convergence times.展开更多
Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers.However,the unbalanced workload of cloud data center network easily leads to the network c...Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers.However,the unbalanced workload of cloud data center network easily leads to the network congestion,the low resource utilization rate,the long delay,the low reliability,and the low throughput.In order to improve the utilization efficiency and the quality of services(QoS)of cloud system,especially to solve the problem of network congestion,we propose MTSS,a multi-path traffic scheduling mechanism based on software defined networking(SDN).MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network.A heuristic traffic balancing algorithm is presented for MTSS,which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing.The experimental results show that MTSS outperforms equal-cost multi-path protocol(ECMP),by effectively reducing the packet loss rate and delay.In addition,MTSS improves the utilization efficiency,the reliability and the throughput rate of the cloud data center network.展开更多
针对传统并行多路传输中数据调度算法存在的问题,基于MPTCP协议,提出了带宽预测和前向时延的数据调度算法(data-scheduling algorithm using bandwidth estimation and forward trip-time,DA-BEFT)。该算法充分考虑子流间传输时延差较...针对传统并行多路传输中数据调度算法存在的问题,基于MPTCP协议,提出了带宽预测和前向时延的数据调度算法(data-scheduling algorithm using bandwidth estimation and forward trip-time,DA-BEFT)。该算法充分考虑子流间传输时延差较大的影响,结合性能好的重传选路策略,减轻接收端因数据乱序导致的缓存阻塞,提高整个连接吞吐量。通过仿真实验验证了DA-BEFT在子流时延差变化时能够提高带宽利用率,提高网络的吞吐量。展开更多
基金supported by the National Natural Science Foundation of China (6120113361172055+6 种基金60832005U083500461072067)the Postdoctoral Science Foundation of China (20100481323)the Program for New Century Excellent Talents (NCET-11-0691)the "111 Project"of China (B08038)the Foundation of Guangxi Key Lab of Wireless Wideband Communication & Signal Processing (11105)
文摘The paper proposes a decentralized concurrent transmission strategy in shared channels based on an incomplete information game in Ad Hoc networks.Based on the nodal channel quality,the game can work out a channel gain threshold,which decides the candidates for taking part in the concurrent transmission.The utility formula is made for maximizing the overall throughput based on channel quality variation.For an achievable Bayesian Nash equilibrium（BNE） solution,this paper further prices the selfish players in utility functions for attempting to improve the channel gain one-sidedly.Accordingly,this game allows each node to distributedly decide whether to transmit concurrently with others depending on the Nash equilibrium（NE）.Besides,to make the proposed game practical,this paper next presents an efficient particle swarm optimization（PSO） model to fasten the otherwise very slow convergence procedure due to the large computational complexity.Numerical results show the proposed approach is feasible to increase concurrent transmission opportunities for active nodes and the convergence can be swiftly obtained with a few of iteration times by the proposed PSO algorithm.
基金supported in part by the National Natural Science Foundation of China under Grant 62171405in part by the National Science Fund for Distinguished Young Scholars under Grant 62225114
文摘With the increasing demand for marine exploration, underwater acoustic sensor networks (UASNs) are prone to have the characteristics of large-scale, long term monitoring, and high data traffic load. Underwater media access control (MAC) protocols, which allow multiple users to share the common medium fairly and efficiently, are essential for the performance of UASNs. However, the design of MAC protocols is confronted with the challenges of spatial unfairness, data eruption, and low energy efficiency. In this paper, we propose a novel data concurrent transmission (DCT) MAC protocol, which is able to exploit long propagation delay and conduct concurrent transmission. Specifically, we present the theoretical performance analysis of the proposed MAC protocol in detail and give an analytical solution of the success concurrent transmission probability between nodes. In addition, simulation results are provided to demonstrate that our proposed protocol is appropriate for UASNs and can significantly improve the performance in terms of network throughput and energy consumption. Finally, we give some typical future applications of UASNs and discuss the demands on MAC protocol design.
文摘The communication in the Millimeter-wave(mmWave)band,i.e.,30~300 GHz,is characterized by short-range transmissions and the use of antenna beamforming(BF).Thus,multiple mmWave access points(APs)should be installed to fully cover a target environment with gigabits per second(Gbps)connectivity.However,inter-beam interference prevents maximizing the sum rates of the established concurrent links.In this paper,a reinforcement learning(RL)approach is proposed for enabling mmWave concurrent transmissions by finding out beam directions that maximize the long-term average sum rates of the concurrent links.Specifically,the problem is formulated as a multiplayer multiarmed bandit(MAB),where mmWave APs act as the players aiming to maximize their achievable rewards,i.e.,data rates,and the arms to play are the available beam directions.In this setup,a selfish concurrent multiplayer MAB strategy is advocated.Four different MAB algorithms,namely,ϵ-greedy,upper confidence bound(UCB),Thompson sampling(TS),and exponential weight algorithm for exploration and exploitation(EXP3)are examined by employing them in each AP to selfishly enhance its beam selection based only on its previous observations.After a few rounds of interactions,mmWave APs learn how to select concurrent beams that enhance the overall system performance.The proposed MAB based mmWave concurrent BF shows comparable performance to the optimal solution.
基金supported by the National Natural Science Foundation of China (60833002)the National Basic Research Program of China (973 Program) (2007CB307100)+2 种基金the National High Technology Research and Development Program of China (863 Program) (2007AA01Z202)the Program for Changjiang Scholars and Innovative Research Team in University (IRT0707)the Program of Introducing Talents of Discipline to Universities (111 Project) (B08002)
文摘Concurrent multipath transfer（CMT） using stream control transmission protocol（SCTP） multihoming has become an appealing option to increase the throughput and improve the performance of increasingly bandwidth-hungry applications.To investigate the rate allocation for applications in CMT,this paper analyzes the capacities of paths shared by competing sources,then proposes the rate allocation model for elastic flows based on the framework of network utility maximization（NUM）.In order to obtain the global optimum of the model,a distributed algorithm is presented which depends only on local available information.Simulation results confirm that the proposed algorithm can achieve the global optimum within reasonable convergence times.
基金supported by the National Key Research and Development Program of China(2018YFB1003702)the National Natural Science Foundation of China(61472192)the Scientific and Technological Support Project(Society)of Jiangsu Province(BE2016776)
文摘Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers.However,the unbalanced workload of cloud data center network easily leads to the network congestion,the low resource utilization rate,the long delay,the low reliability,and the low throughput.In order to improve the utilization efficiency and the quality of services(QoS)of cloud system,especially to solve the problem of network congestion,we propose MTSS,a multi-path traffic scheduling mechanism based on software defined networking(SDN).MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network.A heuristic traffic balancing algorithm is presented for MTSS,which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing.The experimental results show that MTSS outperforms equal-cost multi-path protocol(ECMP),by effectively reducing the packet loss rate and delay.In addition,MTSS improves the utilization efficiency,the reliability and the throughput rate of the cloud data center network.
文摘针对传统并行多路传输中数据调度算法存在的问题,基于MPTCP协议,提出了带宽预测和前向时延的数据调度算法(data-scheduling algorithm using bandwidth estimation and forward trip-time,DA-BEFT)。该算法充分考虑子流间传输时延差较大的影响,结合性能好的重传选路策略,减轻接收端因数据乱序导致的缓存阻塞,提高整个连接吞吐量。通过仿真实验验证了DA-BEFT在子流时延差变化时能够提高带宽利用率,提高网络的吞吐量。
