Energy-aware data aggregation scheme for energy-harvesting wireless sensor networks

In energy-harvesting wireless sensor networks (WSNs), not only energy savings but also efficient energy utilization is required. This study suggests a scheme that indicates when to send data decided by predicting the remaining energy of a node, and aggregates sensed data to increase the amount of data arrived at the sink node. With this method, if the estimated remaining energy of a node is expected to run over the capacity, it transmits aggregated data or else it turns off its radio and only stores sensed data to decrease the blackout time of nodes. Simulation results show that the proposed scheme decreases the blackout time of nodes and increases the data collecting rate efficiently compared to both normal data sending and the specific amount of aggregated data sending cases.

[1]  Jan M. Rabaey,et al.  Power Sources for Wireless Sensor Networks , 2004, EWSN.

[2]  Ivan Stojmenovic,et al.  Handbook of Sensor Networks: Algorithms and Architectures , 2005, Handbook of Sensor Networks.

[3]  Purushottam Kulkarni,et al.  Energy Harvesting Sensor Nodes: Survey and Implications , 2011, IEEE Communications Surveys & Tutorials.

[4]  Wendi B. Heinzelman,et al.  Application-specific protocol architectures for wireless networks , 2000 .

[5]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[6]  R Swetha,et al.  Wireless Sensor Network : A Survey , 2018, IJARCCE.

[7]  Dong Kun Noh,et al.  Minimum Variance Energy Allocation for a Solar-Powered Sensor System , 2009, DCOSS.

[8]  Sanyang Liu,et al.  An Adaptive State-Aware Routing Algorithm for Data Aggregation in Wireless Sensor Networks , 2013, J. Commun..

[9]  Paul J.M. Havinga,et al.  A Dynamic Data Aggregation Scheme for Wireless Sensor Networks , 2003 .

[10]  Pramod K. Varshney,et al.  Data-aggregation techniques in sensor networks: a survey , 2006, IEEE Communications Surveys & Tutorials.

[11]  Dong Kun Noh,et al.  SolarStore: enhancing data reliability in solar-powered storage-centric sensor networks , 2009, MobiSys '09.

[12]  Dario Pompili,et al.  Optimal local topology knowledge for energy efficient geographical routing in sensor networks , 2004, IEEE INFOCOM 2004.

[13]  Dong Kun Noh,et al.  SolarCastalia: Solar Energy Harvesting Wireless Sensor Network Simulator , 2015, Int. J. Distributed Sens. Networks.

[14]  Deborah Estrin,et al.  The impact of data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[15]  Rekha Jain,et al.  Wireless Sensor Network -A Survey , 2013 .

[16]  Jörg Widmer,et al.  In-network aggregation techniques for wireless sensor networks: a survey , 2007, IEEE Wireless Communications.

[17]  Chiara Petrioli,et al.  Pro-Energy: A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks , 2012, 2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012).