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In wireless rechargeable sensor networks, mobile vehicles (MVs) combining energy replenishment and data collection are studied extensively. To reduce data overflow, most recent work has utilized more vehicles to assist the MV to collect buffered data. However, the practical network environment and the limitations of the vehicle in the data collection are not considered. UAV-enabled data collection is immune to complex road environments in remote areas and has higher speed and less traveling cost, which can overcome the lack of the vehicle in data collection. In this paper, a novel framework joining the MV and UAV is proposed to prolong the network lifetime and reduce data overflow. The network lifetime is correlated with the charging order; therefore, we first propose a charging algorithm to find the optimal charging order. During the charging period of the MV, the charging time may be longer than the collecting time. An optimal selection strategy of neighboring clusters, which could send data to the MV, was found to reduce data overflow. Then, to further reduce data overflow, an algorithm is also proposed to schedule the UAV to assist the MV to collect buffered data. Finally, simulation results verified that the proposed algorithms can maximize network lifetime and minimize the data loss simultaneously.
Mengqiu Tian; Wanguo Jiao; Yaqian Chen. A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks. Sensors 2021, 21, 2930 .
AMA StyleMengqiu Tian, Wanguo Jiao, Yaqian Chen. A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks. Sensors. 2021; 21 (9):2930.
Chicago/Turabian StyleMengqiu Tian; Wanguo Jiao; Yaqian Chen. 2021. "A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks." Sensors 21, no. 9: 2930.
In the wireless sensor network, the lifetime of the network can be prolonged by improving the efficiency of limited energy. Existing works achieve better energy utilization, either through node scheduling or routing optimization. In this paper, an efficient solution combining node scheduling with routing protocol optimization is proposed in order to improve the network lifetime. Firstly, to avoid the redundant coverage, a node scheduling scheme that is based on a genetic algorithm is proposed to find the minimum number of sensor nodes to monitor all target points. Subsequently, the algorithm prolongs the lifetime of the network through choosing redundant sleep nodes to replace the dead node. Based on the obtained minimum coverage set, a new routing protocol, named Improved-Distributed Energy-Efficient Clustering (I-DEEC), is proposed. When considering the energy and the distance of the sensor node to the sink, a new policy choosing the cluster head is proposed. To make the energy load more balanced, uneven clusters are constructed. Meanwhile, the data communication way of sensor nodes around the sink is also optimized. The simulation results show that the proposed sensor node scheduling algorithm can reduce the number of redundant sensor nodes, while the I-DEEC routing protocol can improve the energy efficiency of data transmission. The lifetime of the network is greatly extended.
Yun Xu; Wanguo Jiao; Mengqiu Tian. Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks. Sensors 2020, 20, 6127 .
AMA StyleYun Xu, Wanguo Jiao, Mengqiu Tian. Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks. Sensors. 2020; 20 (21):6127.
Chicago/Turabian StyleYun Xu; Wanguo Jiao; Mengqiu Tian. 2020. "Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks." Sensors 20, no. 21: 6127.
Recently, wireless energy transfer technology becomes a popular way to address energy shortage in wireless sensor networks. The capacity of the mobile wireless charging car (WCV) and the wireless channel between the WCV and the sensor are two important factors influencing the energy efficiency of the wireless sensor network, which has not been well considered. In this paper, we study the energy efficiency of a wireless rechargeable sensor network charged by a finite capacity WCV through an imperfect wireless channel. To estimate the energy efficiency, we first propose a new metric named waste rate, which is defined as a function of the charging channel quality. Then, energy efficiency optimization is modeled as minimizing the waste rate. Through optimizing the distance between the WCV and sensor nodes, the set of optimal charging sensor nodes is obtained. By using the Hamiltonian circle, the nearest neighbor algorithm is proposed to find the traveling path of the WCV. Furthermore, to avoid the untimely death of sensor nodes and the coverage hole, an extended node dynamic replacement strategy is proposed. The simulation results show that the proposed method can reduce the waste rate and the total charging time; i.e., the sum of traveling time and charging delay can be significantly reduced, which indicates that the proposed algorithm can improve the energy efficiency of the network.
Mengqiu Tian; Wanguo Jiao; Jiaming Liu; Siyuan Ma. A Charging Algorithm for the Wireless Rechargeable Sensor Network with Imperfect Charging Channel and Finite Energy Storage. Sensors 2019, 19, 3887 .
AMA StyleMengqiu Tian, Wanguo Jiao, Jiaming Liu, Siyuan Ma. A Charging Algorithm for the Wireless Rechargeable Sensor Network with Imperfect Charging Channel and Finite Energy Storage. Sensors. 2019; 19 (18):3887.
Chicago/Turabian StyleMengqiu Tian; Wanguo Jiao; Jiaming Liu; Siyuan Ma. 2019. "A Charging Algorithm for the Wireless Rechargeable Sensor Network with Imperfect Charging Channel and Finite Energy Storage." Sensors 19, no. 18: 3887.