Wireless sensor networks (WSNs) have the trouble of limited battery power, and wireless charging provides apromising solution to this problem, which is not easily affected by the external environment. In this paper, w...Wireless sensor networks (WSNs) have the trouble of limited battery power, and wireless charging provides apromising solution to this problem, which is not easily affected by the external environment. In this paper, we studythe recharging of sensors in wireless rechargeable sensor networks (WRSNs) by scheduling two mobile chargers(MCs) to collaboratively charge sensors. We first formulate a novel sensor charging scheduling problem with theobjective of maximizing the number of surviving sensors, and further propose a collaborative charging schedulingalgorithm(CCSA) for WRSNs. In the scheme, the sensors are divided into important sensors and ordinary sensors.TwoMCs can adaptively collaboratively charge the sensors based on the energy limit ofMCs and the energy demandof sensors. Finally, we conducted comparative simulations. The simulation results show that the proposed algorithmcan effectively reduce the death rate of the sensor. The proposed algorithm provides a solution to the uncertaintyof node charging tasks and the collaborative challenges posed by multiple MCs in practical scenarios.展开更多
In rechargeable wireless sensor networks, a sensor cannot be always benefi cial to conserve energy when a network can harvest excessive energy from the environment due to its energy replenished continually and limited...In rechargeable wireless sensor networks, a sensor cannot be always benefi cial to conserve energy when a network can harvest excessive energy from the environment due to its energy replenished continually and limited energy storage capacity. Therefore, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving data collection rate. In this work, we propose an algorithm to compute an upper data generation rate that maximizes it as an optimization problem for a network with multiple sinks, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms are guaranteed to converge to an optimal data generation rate, which are illustrated by an example in which an optimum data generation rate is computed for a network of randomly distributed nodes. Through extensive simulation and experiments, we demonstrate our algorithm is efficient to maximize data collection rate in rechargeable wireless sensor networks.展开更多
As the technological breakthrough is made in wireless charging, the wireless rechargeable sensor networks (WRSNs) are finally proposed. In order to reduce the charging completion time, most existing works use the “mo...As the technological breakthrough is made in wireless charging, the wireless rechargeable sensor networks (WRSNs) are finally proposed. In order to reduce the charging completion time, most existing works use the “mobilethen- charge” model—the Wireless charging vehicles (WCV) moves to the charging spot first and then charges nodes nearby. These works often aim to reduce the node’s movement delay or charging delay. However, the charging opportunities during the movement are overlooked in this model because WCV can charge nodes when it goes from one spot to the next. In order to use the charging opportunities, a speed grading method is proposed under the circumstance of variable WCV speed, which transformed the problem of final charging delay into a traveling salesman problem with speed grading. The problem was further solved by linear programming method. The simulation experiments show that, compared with the existing charging methods, the proposed method has a significant improvement in charging delay.展开更多
针对无线可充电传感器网络(WRSN)中的节点死亡率过高问题,为了降低节点死亡率,以按需充电架构为基础,提出了一种动态不均匀分簇的单移动充电设备(MC)多节点在线充电策略SMMCS(single MC multi-node charging strategy)。策略首先将无线...针对无线可充电传感器网络(WRSN)中的节点死亡率过高问题,为了降低节点死亡率,以按需充电架构为基础,提出了一种动态不均匀分簇的单移动充电设备(MC)多节点在线充电策略SMMCS(single MC multi-node charging strategy)。策略首先将无线可充电传感器网络进行动态不均匀分簇,以此划分移动充电设备的服务分区;然后在此模型基础上以最小网络节点死亡率为目标,进行路径规划时综合考虑节点剩余能量、距离以及能耗等因素。仿真实验结果表明,与SAMER、VTMT以及FCFS策略相比,该策略减少了节点等待时间,缩短了MC总充电代价,减小了节点死亡率。基于仿真条件,网络节点死亡率为4.31%。展开更多
新型无线可充电传感器网络中无线充电小车的充电调度算法研究,针对网络中传感器节点发出的充电请求,进行Revised Earliest Deadline First(REDF)无线充电调度优化算法设计。REDF算法综合考虑充电期限和节点距离两个制约因素,使得每一个...新型无线可充电传感器网络中无线充电小车的充电调度算法研究,针对网络中传感器节点发出的充电请求,进行Revised Earliest Deadline First(REDF)无线充电调度优化算法设计。REDF算法综合考虑充电期限和节点距离两个制约因素,使得每一个传感器的充电需求都能得到及时满足,并且无线充电小车还能够在较短的时间内完成充电工作,从而延长无线传感器网络生命周期,建立一个稳定供应能量的无线传感器网络。算法的性能仿真结果表明,REDF算法的性能要优于Earliest Due Date First(EDDF)。展开更多
基金Hubei Provincial Natural Science Foundation of China under Grant No.2017CKB893Wuhan Polytechnic University Reform Subsidy Project Grant No.03220153.
文摘Wireless sensor networks (WSNs) have the trouble of limited battery power, and wireless charging provides apromising solution to this problem, which is not easily affected by the external environment. In this paper, we studythe recharging of sensors in wireless rechargeable sensor networks (WRSNs) by scheduling two mobile chargers(MCs) to collaboratively charge sensors. We first formulate a novel sensor charging scheduling problem with theobjective of maximizing the number of surviving sensors, and further propose a collaborative charging schedulingalgorithm(CCSA) for WRSNs. In the scheme, the sensors are divided into important sensors and ordinary sensors.TwoMCs can adaptively collaboratively charge the sensors based on the energy limit ofMCs and the energy demandof sensors. Finally, we conducted comparative simulations. The simulation results show that the proposed algorithmcan effectively reduce the death rate of the sensor. The proposed algorithm provides a solution to the uncertaintyof node charging tasks and the collaborative challenges posed by multiple MCs in practical scenarios.
基金supported by The Natural Science Foundation of Jiangsu Province of China(Grant No.BK20141474)funded by China Postdoctoral Science Foundation(Grant No.2015M571639)+3 种基金three Projects Funded by The Jiangsu Planned Projects for Postdoctoral Research Funds(Grant No.1402018C)The Key Laboratory of Computer Network and Information Integration(Southeast University)Ministry of Education(Grant No.K93-9-2015-09C)The Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions
文摘In rechargeable wireless sensor networks, a sensor cannot be always benefi cial to conserve energy when a network can harvest excessive energy from the environment due to its energy replenished continually and limited energy storage capacity. Therefore, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving data collection rate. In this work, we propose an algorithm to compute an upper data generation rate that maximizes it as an optimization problem for a network with multiple sinks, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms are guaranteed to converge to an optimal data generation rate, which are illustrated by an example in which an optimum data generation rate is computed for a network of randomly distributed nodes. Through extensive simulation and experiments, we demonstrate our algorithm is efficient to maximize data collection rate in rechargeable wireless sensor networks.
文摘As the technological breakthrough is made in wireless charging, the wireless rechargeable sensor networks (WRSNs) are finally proposed. In order to reduce the charging completion time, most existing works use the “mobilethen- charge” model—the Wireless charging vehicles (WCV) moves to the charging spot first and then charges nodes nearby. These works often aim to reduce the node’s movement delay or charging delay. However, the charging opportunities during the movement are overlooked in this model because WCV can charge nodes when it goes from one spot to the next. In order to use the charging opportunities, a speed grading method is proposed under the circumstance of variable WCV speed, which transformed the problem of final charging delay into a traveling salesman problem with speed grading. The problem was further solved by linear programming method. The simulation experiments show that, compared with the existing charging methods, the proposed method has a significant improvement in charging delay.
文摘针对无线可充电传感器网络(WRSN)中的节点死亡率过高问题,为了降低节点死亡率,以按需充电架构为基础,提出了一种动态不均匀分簇的单移动充电设备(MC)多节点在线充电策略SMMCS(single MC multi-node charging strategy)。策略首先将无线可充电传感器网络进行动态不均匀分簇,以此划分移动充电设备的服务分区;然后在此模型基础上以最小网络节点死亡率为目标,进行路径规划时综合考虑节点剩余能量、距离以及能耗等因素。仿真实验结果表明,与SAMER、VTMT以及FCFS策略相比,该策略减少了节点等待时间,缩短了MC总充电代价,减小了节点死亡率。基于仿真条件,网络节点死亡率为4.31%。
文摘新型无线可充电传感器网络中无线充电小车的充电调度算法研究,针对网络中传感器节点发出的充电请求,进行Revised Earliest Deadline First(REDF)无线充电调度优化算法设计。REDF算法综合考虑充电期限和节点距离两个制约因素,使得每一个传感器的充电需求都能得到及时满足,并且无线充电小车还能够在较短的时间内完成充电工作,从而延长无线传感器网络生命周期,建立一个稳定供应能量的无线传感器网络。算法的性能仿真结果表明,REDF算法的性能要优于Earliest Due Date First(EDDF)。
