In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management str...In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.展开更多
Unmanned aerial vehicles(UAVs) are increasingly considered in safe autonomous navigation systems to explore unknown environments where UAVs are equipped with multiple sensors to perceive the surroundings. However, how...Unmanned aerial vehicles(UAVs) are increasingly considered in safe autonomous navigation systems to explore unknown environments where UAVs are equipped with multiple sensors to perceive the surroundings. However, how to achieve UAVenabled data dissemination and also ensure safe navigation synchronously is a new challenge. In this paper, our goal is minimizing the whole weighted sum of the UAV’s task completion time while satisfying the data transmission task requirement and the UAV’s feasible flight region constraints. However, it is unable to be solved via standard optimization methods mainly on account of lacking a tractable and accurate system model in practice. To overcome this tough issue,we propose a new solution approach by utilizing the most advanced dueling double deep Q network(dueling DDQN) with multi-step learning. Specifically, to improve the algorithm, the extra labels are added to the primitive states. Simulation results indicate the validity and performance superiority of the proposed algorithm under different data thresholds compared with two other benchmarks.展开更多
提出了一种DTN多源多宿网络的数据编码分发机制(Data Dissemination Mechanism with Network Coding Based on Ant Colony Algorithm,DDM-NC).在发布/订阅机制的基础上,通过对主题数据的编码运算和传输,充分利用网络容量进行数据多播,...提出了一种DTN多源多宿网络的数据编码分发机制(Data Dissemination Mechanism with Network Coding Based on Ant Colony Algorithm,DDM-NC).在发布/订阅机制的基础上,通过对主题数据的编码运算和传输,充分利用网络容量进行数据多播,使得数据传输具有更好的安全性和传输效率;同时,针对编码包洪泛传输过程中信息冗余大,无效投递较多等问题,设计了基于蚁群算法的编码包路由策略,引导编码包向信宿聚集,降低编码投递过程中的数据冗余,减少投递延迟.仿真实验表明,相比传统的DTN传染病路由策略和随机网络编码传输方法,DDM-NC方法有更好的数据投递性能.展开更多
移动低占空比无线传感器网络是近年来出现的新型网络。在移动低占空比无线传感器网络中,由于节点的存储空间有限,并且节点的移动及睡眠会导致网络不连通、数据无法及时传输等问题,使数据很难被快速分发并存储,数据持续性较低。为此,提...移动低占空比无线传感器网络是近年来出现的新型网络。在移动低占空比无线传感器网络中,由于节点的存储空间有限,并且节点的移动及睡眠会导致网络不连通、数据无法及时传输等问题,使数据很难被快速分发并存储,数据持续性较低。为此,提出一种卢比变换码的分布式数据存储(LT-MDS,Luby transform codes based mobile distributed storage)算法,该算法采用一种新的传染病式数据分发方法在节点不断移动的网络中分发数据,使数据能以较低的时延被网络中绝大部分节点接收到,提高了网络的可靠性;节点在接收到数据的同时,利用卢比变换码(LTC,Luby transform code)对数据进行编码存储,使容量有限的节点可以保存更多的数据信息。理论分析和仿真实验表明,LT-MDS算法能够以低时延完成数据分发和存储,同时获得较高的数据持续性。展开更多
基金supported by the National Natural Science Fund of China under Grant No. 61472097the Education Ministry Doctoral Research Foundation of China (20132304110017)the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation
文摘In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.
基金supported by the National Natural Science Foundation of China (No. 61931011)。
文摘Unmanned aerial vehicles(UAVs) are increasingly considered in safe autonomous navigation systems to explore unknown environments where UAVs are equipped with multiple sensors to perceive the surroundings. However, how to achieve UAVenabled data dissemination and also ensure safe navigation synchronously is a new challenge. In this paper, our goal is minimizing the whole weighted sum of the UAV’s task completion time while satisfying the data transmission task requirement and the UAV’s feasible flight region constraints. However, it is unable to be solved via standard optimization methods mainly on account of lacking a tractable and accurate system model in practice. To overcome this tough issue,we propose a new solution approach by utilizing the most advanced dueling double deep Q network(dueling DDQN) with multi-step learning. Specifically, to improve the algorithm, the extra labels are added to the primitive states. Simulation results indicate the validity and performance superiority of the proposed algorithm under different data thresholds compared with two other benchmarks.
文摘提出了一种DTN多源多宿网络的数据编码分发机制(Data Dissemination Mechanism with Network Coding Based on Ant Colony Algorithm,DDM-NC).在发布/订阅机制的基础上,通过对主题数据的编码运算和传输,充分利用网络容量进行数据多播,使得数据传输具有更好的安全性和传输效率;同时,针对编码包洪泛传输过程中信息冗余大,无效投递较多等问题,设计了基于蚁群算法的编码包路由策略,引导编码包向信宿聚集,降低编码投递过程中的数据冗余,减少投递延迟.仿真实验表明,相比传统的DTN传染病路由策略和随机网络编码传输方法,DDM-NC方法有更好的数据投递性能.
文摘移动低占空比无线传感器网络是近年来出现的新型网络。在移动低占空比无线传感器网络中,由于节点的存储空间有限,并且节点的移动及睡眠会导致网络不连通、数据无法及时传输等问题,使数据很难被快速分发并存储,数据持续性较低。为此,提出一种卢比变换码的分布式数据存储(LT-MDS,Luby transform codes based mobile distributed storage)算法,该算法采用一种新的传染病式数据分发方法在节点不断移动的网络中分发数据,使数据能以较低的时延被网络中绝大部分节点接收到,提高了网络的可靠性;节点在接收到数据的同时,利用卢比变换码(LTC,Luby transform code)对数据进行编码存储,使容量有限的节点可以保存更多的数据信息。理论分析和仿真实验表明,LT-MDS算法能够以低时延完成数据分发和存储,同时获得较高的数据持续性。
