针对DV_Hop(Distance Vector-Hop)算法中定位精度较低的问题,提出一种基于最优跳距与LevyPSO算法的无线传感器网络定位算法,即OLPDV_Hop(Optimal Jump Distance and Levy Particle Swarm Optimization DV_Hop)。首先,通过单跳平均误差...针对DV_Hop(Distance Vector-Hop)算法中定位精度较低的问题,提出一种基于最优跳距与LevyPSO算法的无线传感器网络定位算法,即OLPDV_Hop(Optimal Jump Distance and Levy Particle Swarm Optimization DV_Hop)。首先,通过单跳平均误差修正平均跳距,然后利用接收多锚节点的平均跳距估算节点间距离,使估算距离得以优化,最后利用LevyPSO算法替代最小二乘法求得未知节点位置,LevyPSO算法利用Levy飞行改变粒子移动方向以防陷入局部最优,并通过贪婪的更新评价策略产生最优解,最终得到全局最优。仿真结果表明,OLPDV_Hop算法较DV_Hop算法、IPSODV_Hop(Improved Particle Swarm Optimization DV_Hop)算法和BDV_Hop(Based on DV_Hop)算法在定位精度上有明显改善。展开更多
为了描绘和减轻无线传感器网络中的"热区"与降低路由能耗,提出了一种基于最优跳数的非均匀分簇算法UCOH(Uneven clustering routing algorithm based on optimal hops).本文首先推导了使节点直线传输数据到基站总能耗最小时...为了描绘和减轻无线传感器网络中的"热区"与降低路由能耗,提出了一种基于最优跳数的非均匀分簇算法UCOH(Uneven clustering routing algorithm based on optimal hops).本文首先推导了使节点直线传输数据到基站总能耗最小时的最优跳数,得到路由消耗最小的理想路径;然后,所提算法根据该理想路径形成的热区引入入簇半径调整簇规模,以平衡节点出任簇头时的簇内和路由中继能耗;最后,在保证能耗均衡的前提下,选择邻居候选簇头中较符合理想路径的节点作为下一跳中继节点,进一步降低能耗速率.仿真结果显示,针对节点密度较大的网络,本算法较DEBUC、UCDP、SNNUC算法延长了以30%节点死亡为网络失效的网络生命周期,表明算法能有效地降低节点能耗和减轻热区效应.展开更多
为了提高DV-Hop(Distance Vector-Hop)算法中无线传感器网络节点定位精度,提出一种基于OLPDV-Hop(Optimal Jump Distance and Levy Particle Swarm Optimization DV-Hop)的节点定位算法,对OLPDV-Hop算法选择Windows7的MATLABR2014a系统...为了提高DV-Hop(Distance Vector-Hop)算法中无线传感器网络节点定位精度,提出一种基于OLPDV-Hop(Optimal Jump Distance and Levy Particle Swarm Optimization DV-Hop)的节点定位算法,对OLPDV-Hop算法选择Windows7的MATLABR2014a系统环境依次对比了DV-Hop、BDV-Hop与IPSODV-Hop三种算法比较。在节点总数等于100、锚节点数占比为20%以及25~50m通信半径范围内,算法平均定位误差都发生了减小的情况,之后开始重新升高。四种算法都发生了平均定位误差不断降低的现象,当锚节点的密度上升后,相互间的跳数将会变小,并且OLPDV-Hop算法达到最小的平均定位误差。展开更多
In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper...In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.展开更多
This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backw...This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.展开更多
Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both dif...Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form.展开更多
This paper studies the existence and uniqueness of solutions of fully coupled forward-backward stochastic differential equations with Brownian motion and random jumps.The result is applied to solve a linear-quadratic ...This paper studies the existence and uniqueness of solutions of fully coupled forward-backward stochastic differential equations with Brownian motion and random jumps.The result is applied to solve a linear-quadratic optimal control and a nonzero-sum differential game of backward stochastic differential equations.The optimal control and Nash equilibrium point are explicitly derived. Also the solvability of a kind Riccati equations is discussed.All these results develop those of Lim, Zhou(2001) and Yu,Ji(2008).展开更多
文摘为了描绘和减轻无线传感器网络中的"热区"与降低路由能耗,提出了一种基于最优跳数的非均匀分簇算法UCOH(Uneven clustering routing algorithm based on optimal hops).本文首先推导了使节点直线传输数据到基站总能耗最小时的最优跳数,得到路由消耗最小的理想路径;然后,所提算法根据该理想路径形成的热区引入入簇半径调整簇规模,以平衡节点出任簇头时的簇内和路由中继能耗;最后,在保证能耗均衡的前提下,选择邻居候选簇头中较符合理想路径的节点作为下一跳中继节点,进一步降低能耗速率.仿真结果显示,针对节点密度较大的网络,本算法较DEBUC、UCDP、SNNUC算法延长了以30%节点死亡为网络失效的网络生命周期,表明算法能有效地降低节点能耗和减轻热区效应.
文摘为了提高DV-Hop(Distance Vector-Hop)算法中无线传感器网络节点定位精度,提出一种基于OLPDV-Hop(Optimal Jump Distance and Levy Particle Swarm Optimization DV-Hop)的节点定位算法,对OLPDV-Hop算法选择Windows7的MATLABR2014a系统环境依次对比了DV-Hop、BDV-Hop与IPSODV-Hop三种算法比较。在节点总数等于100、锚节点数占比为20%以及25~50m通信半径范围内,算法平均定位误差都发生了减小的情况,之后开始重新升高。四种算法都发生了平均定位误差不断降低的现象,当锚节点的密度上升后,相互间的跳数将会变小,并且OLPDV-Hop算法达到最小的平均定位误差。
基金supported by the National Natural Science Foundation of China under Grants No.60972038,No.61001077,No.61101105 the Scientific Research Foundation for Nanjing University of Posts and Telecommunications under Grant No.NY211007+2 种基金 the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2011D05 Specialized Research Fund for the Doctoral Program of Higher Education under Grant No.20113223120002 University Natural Science Research Project of Jiangsu Province under Grant No.11KJB510016
文摘In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.
基金This research is supported by the National Nature Science Foundation of China under Grant Nos 11001156, 11071144, the Nature Science Foundation of Shandong Province （ZR2009AQ017）, and Independent Innovation Foundation of Shandong University （IIFSDU）, China.
文摘This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.
基金supported by the National Basic Research Program of China (973 Program) under Grant No.2007CB814904the National Natural Science Foundations of China under Grant Nos.10921101 and 10701050the Natural Science Foundation of Shandong Province under Grant Nos.JQ200801 and 2008BS01024
文摘Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form.
基金supported by National Natural Science Foundation of China(10671112)National Basic Research Program of China(973 Program)(2007CB814904)the Natural Science Foundation of Shandong Province(Z2006A01)
文摘This paper studies the existence and uniqueness of solutions of fully coupled forward-backward stochastic differential equations with Brownian motion and random jumps.The result is applied to solve a linear-quadratic optimal control and a nonzero-sum differential game of backward stochastic differential equations.The optimal control and Nash equilibrium point are explicitly derived. Also the solvability of a kind Riccati equations is discussed.All these results develop those of Lim, Zhou(2001) and Yu,Ji(2008).
