Optimal energy replenishment and data collection in wireless rechargeable sensor networks

2014 ◽  
Author(s):  
Miao Pan ◽  
Hongyan Li ◽  
Yawei Pang ◽  
Rong Yu ◽  
Zaixin Lu ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Data Collection ◽  
Optimal Energy ◽  
Wireless Rechargeable Sensor Networks ◽  
Energy Replenishment

scholarly journals A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2930
Author(s):  
Mengqiu Tian ◽  
Wanguo Jiao ◽  
Yaqian Chen
Keyword(s):  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Selection Strategy ◽  
Data Loss ◽  
Remote Areas ◽  
Charging Time ◽  
Data Collection Strategy ◽  
Wireless Rechargeable Sensor Networks ◽  
Energy Replenishment

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.

scholarly journals A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3150 ◽  
Author(s):  
Chao Sha ◽  
Qin Liu ◽  
Si-Yi Song ◽  
Ru-Chuan Wang
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Energy Hole ◽  
Node Scheduling ◽  
Wireless Rechargeable Sensor Networks ◽  
Energy Consumption Optimization ◽  
Balance Energy ◽  
Simulation Results

With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.

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