An Analysis Scheme of Balancing Energy Consumption with Mobile Velocity Control Strategy for Wireless Rechargeable Sensor Networks

Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and expenditure of nodes. A minimum reliable energy balanced spanning tree is constructed based on data collection to optimize the data transmission paths, balance energy consumption, and reduce data loss during transmission. Experimental results are compared with the other methods in the literature that show that the proposed scheme offers a more effective alternative in reducing the network packet loss rate, balancing the nodes’ energy consumption, and charging capacity of the nodes than the competitors.

[1]  Neelesh B. Mehta,et al.  Revisiting Effectiveness of Energy Conserving Opportunistic Transmission Schemes in Energy Harvesting Wireless Sensor Networks , 2019, IEEE Transactions on Communications.

[2]  Jeng-Shyang Pan,et al.  An Improved Flower Pollination Algorithm for Optimizing Layouts of Nodes in Wireless Sensor Network , 2019, IEEE Access.

[3]  Jeng-Shyang Pan,et al.  An Optimal Node Coverage in Wireless Sensor Network Based on Whale Optimization Algorithm , 2019 .

[4]  Weifa Liang,et al.  Efficient Algorithms for Mobile Sink Aided Data Collection From Dedicated and Virtual Aggregation Nodes in Energy Harvesting Wireless Sensor Networks , 2019, IEEE Transactions on Green Communications and Networking.

[5]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[6]  Jin Wang,et al.  An Adaptation Multi-Group Quasi-Affine Transformation Evolutionary Algorithm for Global Optimization and Its Application in Node Localization in Wireless Sensor Networks , 2019, Sensors.

[7]  Chang Zhou,et al.  Optimal Coverage Multi-Path Scheduling Scheme with Multiple Mobile Sinks for WSNs , 2020 .

[8]  Trong-The Nguyen,et al.  An Energy-based Cluster Head Selection Algorithm to Support Long-lifetime in Wireless Sensor Networks , 2016, J. Netw. Intell..

[9]  Qingchun Chen,et al.  Adaptive Transmission Design for Rechargeable Wireless Sensor Network With a Mobile Sink , 2020, IEEE Internet of Things Journal.

[10]  Djamel Djenouri,et al.  Efficient on-demand multi-node charging techniques for wireless sensor networks , 2017, Comput. Commun..

[11]  Trong-The Nguyen,et al.  A Hybrid Improved MVO and FNN for Identifying Collected Data Failure in Cluster Heads in WSN , 2020, IEEE Access.

[12]  Jinjun Chen,et al.  Speed control of mobile chargers serving wireless rechargeable networks , 2018, Future Gener. Comput. Syst..

[13]  Trong-The Nguyen,et al.  Identification Failure Data for Cluster Heads Aggregation in WSN Based on Improving Classification of SVM , 2020, IEEE Access.

[14]  Prasant Mohapatra,et al.  Medium access control in wireless sensor networks , 2007, Comput. Networks.

[15]  Guang-Dong Zhou,et al.  Recent Developments on Wireless Sensor Networks Technology for Bridge Health Monitoring , 2013 .

[16]  Cong Wang,et al.  Mobile data gathering with Wireless Energy Replenishment in rechargeable sensor networks , 2013, 2013 Proceedings IEEE INFOCOM.

[17]  Xuemin Shen,et al.  Optimal Reliability in Energy Harvesting Industrial Wireless Sensor Networks , 2016, IEEE Transactions on Wireless Communications.

[18]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[19]  Yuanyuan Yang,et al.  A Framework of Joint Mobile Energy Replenishment and Data Gathering in Wireless Rechargeable Sensor Networks , 2014, IEEE Transactions on Mobile Computing.

[20]  Song Han,et al.  Mobile data gathering and energy harvesting in rechargeable wireless sensor networks , 2019, Inf. Sci..

[21]  Jin Wang,et al.  Big Data Service Architecture: A Survey , 2020 .

[22]  Yuanyuan Yang,et al.  Energy Efficiency Maximization in Mobile Wireless Energy Harvesting Sensor Networks , 2018, IEEE Transactions on Mobile Computing.

[23]  Rathinasamy Sakthivel,et al.  Energy-efficient data collection in strip-based wireless sensor networks with optimal speed mobile data collectors , 2019, Comput. Networks.

[24]  Mohammad S. Obaidat,et al.  TSCA: A Temporal-Spatial Real-Time Charging Scheduling Algorithm for On-Demand Architecture in Wireless Rechargeable Sensor Networks , 2018, IEEE Transactions on Mobile Computing.

[25]  Wendi B. Heinzelman,et al.  Energy-Harvesting Wireless Sensor Networks (EH-WSNs) , 2018, ACM Trans. Sens. Networks.

[26]  Trong-The Nguyen,et al.  Identifying correctness data scheme for aggregating data in cluster heads of wireless sensor network based on naive Bayes classification , 2020, EURASIP Journal on Wireless Communications and Networking.

[27]  Kay Römer,et al.  A Decade of Wireless Sensing Applications: Survey and Taxonomy , 2014 .

[28]  Guangjie Han,et al.  A Joint Energy Replenishment and Data Collection Algorithm in Wireless Rechargeable Sensor Networks , 2018, IEEE Internet of Things Journal.

[29]  Arun Kumar Sangaiah,et al.  An Improved Routing Schema with Special Clustering Using PSO Algorithm for Heterogeneous Wireless Sensor Network , 2019, Sensors.

[30]  Avijit Mathur,et al.  Defence against Black Hole and Selective Forwarding Attacks for Medical WSNs in the IoT , 2016, Sensors.

[31]  Trong-The Nguyen,et al.  A Novel Improved Bat Algorithm Based on Hybrid Parallel and Compact for Balancing an Energy Consumption Problem , 2019, Inf..

[32]  Vinod Sharma,et al.  Optimal energy management policies for energy harvesting sensor nodes , 2008, IEEE Transactions on Wireless Communications.

[33]  Trong-The Nguyen,et al.  Clustering Formation in Wireless Sensor Networks: A Survey , 2017, J. Netw. Intell..

[34]  Trong-The Nguyen,et al.  A Compact Bat Algorithm for Unequal Clustering in Wireless Sensor Networks , 2019, Applied Sciences.