A Hybrid Control Law for Energy-Oriented Tasks Scheduling in Wireless Sensor Networks

Energy is a key resource in wireless sensor networks (WSNs), especially when sensor nodes are powered by batteries. This paper investigates how to save energy of the whole WSN, thanks to control strategies, in real time and in a dynamic way. The energy management strategy is based on a hybrid dynamical system approach. This choice is motivated by the hybrid inherent nature of the WSN system when energy management is considered. The hybrid nature basically comes from the combination of continuous physical processes, namely, the charge/discharge of the node batteries, while the discrete part is related to the change in the functioning modes and an unreachable condition of the nodes. This approach provides a decentralized controller with low computational load that reduces the number of switching as compared with existing approaches. The proposed strategy is evaluated and compared in simulation on a realistic test case. Last, they have been implemented on a real test bench, and the obtained results have been discussed.

[1]  Maxime Louvel,et al.  LINC: A Compact Yet Powerful Coordination Environment , 2014, COORDINATION.

[2]  Mario Di Francesco,et al.  Energy conservation in wireless sensor networks: A survey , 2009, Ad Hoc Networks.

[3]  Shu Du,et al.  RMAC: A Routing-Enhanced Duty-Cycle MAC Protocol for Wireless Sensor Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[4]  Angelo Perkusich,et al.  Dynamic Power Management with Scheduled Switching Modes , 2008, Comput. Commun..

[5]  Fabien Clermidy,et al.  Asynchronous Circuit Designs for the Internet of Everything: A Methodology for Ultralow-Power Circuits with GALS Architecture , 2016, IEEE Solid-State Circuits Magazine.

[6]  Ricardo G. Sanfelice,et al.  Hybrid Dynamical Systems: Modeling, Stability, and Robustness , 2012 .

[7]  F. Pacull,et al.  Resource-based middleware in the context of heterogeneous building automation systems , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[8]  Jean-Marie Bonnin,et al.  Wireless sensor networks: a survey on recent developments and potential synergies , 2013, The Journal of Supercomputing.

[9]  Catherine Rosenberg,et al.  Homogeneous vs heterogeneous clustered sensor networks: a comparative study , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

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

[11]  Daniel E. Quevedo,et al.  Energy Efficient State Estimation With Wireless Sensors Through the Use of Predictive Power Control and Coding , 2010, IEEE Transactions on Signal Processing.

[12]  Olesia Mokrenko,et al.  Design and Implementation of a Predictive Control Strategy for Power Management of a Wireless Sensor Network , 2019 .

[13]  Anantha Chandrakasan,et al.  Dynamic Power Management in Wireless Sensor Networks , 2001, IEEE Des. Test Comput..

[14]  Ricardo G. Sanfelice,et al.  A toolbox for simulation of hybrid systems in matlab/simulink: hybrid equations (HyEQ) toolbox , 2013, HSCC '13.

[15]  Shen Yan,et al.  Dynamic power management of wireless sensor networks based on grey model , 2010, 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE).

[16]  Aylin Yener,et al.  Sum-rate optimal power policies for energy harvesting transmitters in an interference channel , 2011, Journal of Communications and Networks.

[17]  Olesia Mokrenko,et al.  Energy management of a wireless sensor network at application level , 2015 .

[18]  Olesia Mokrenko,et al.  WSN power management with battery capacity estimation , 2015, 2015 IEEE 13th International New Circuits and Systems Conference (NEWCAS).

[19]  Alberto Bemporad,et al.  Energy-aware robust model predictive control based on noisy wireless sensors , 2012, Autom..

[20]  Nagendra Prasad Mandru.  OPTIMAL POWER MANAGEMENT IN WIRELESS SENSOR NETWORKS FOR ENHANCED LIFE TIME , 2012 .

[21]  Olesia Mokrenko,et al.  Dynamic power management in a wireless sensor network using predictive control , 2014, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society.