Optimal performance trade-offs in MAC for wireless sensor networks powered by heterogeneous ambient energy harvesting

In wireless sensor networks powered by ambient energy harvesting (WSNs-HEAP), sensor nodes' energy harvesting rates are spatially heterogeneous and temporally variant, which impose difficulties for medium access control (MAC). In this paper, we first derive the necessary conditions under which channel utilization and fairness are optimal in a WSN-HEAP, respectively. Based on the analysis, we propose an earliest deadline first (EDF) polling MAC protocol, which regulates transmission sequence of the sensor nodes based on the spatially heterogeneous energy harvesting rates. It also mitigates temporal variations in energy harvesting rates by a prediction and update mechanism. Simulation results verify the performance tradeoff predicted by our analysis for the proposed HEAP-EDF protocol. In the presence of spatial heterogeneity and temporal variations in energy harvesting rates, our proposed protocol exhibits significant performance advantages compared to the existing MAC protocols for WSNs-HEAP in the literature.

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

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

[3]  Srikanth V. Krishnamurthy,et al.  Polling-based media access protocols for use with smart adaptive array antennas , 2001, TNET.

[4]  Charles R. Farrar,et al.  Energy Harvesting for Structural Health Monitoring Sensor Networks , 2008 .

[5]  Luca Benini,et al.  Real-time scheduling for energy harvesting sensor nodes , 2007, Real-Time Systems.

[6]  Venugopal V. Veeravalli,et al.  Energy Efficient Multi-Object Tracking in Sensor Networks , 2010, IEEE Transactions on Signal Processing.

[7]  Jing Yang,et al.  Optimal Packet Scheduling in an Energy Harvesting Communication System , 2010, IEEE Transactions on Communications.

[8]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[9]  Yuping Zhao,et al.  Analysis and Compare of Slotted and Unslotted CSMA in IEEE 802.15.4 , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[10]  C. K. Michael Tse,et al.  An Energy-Aware Scheduling Scheme for Wireless Sensor Networks , 2010, IEEE Transactions on Vehicular Technology.

[11]  Hwee Pink Tan,et al.  Empirical modeling of a solar-powered energy harvesting wireless sensor node for time-slotted operation , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[12]  Andrea Conti,et al.  Mathematical Evaluation of Environmental Monitoring Estimation Error through Energy-Efficient Wireless Sensor Networks , 2007, IEEE Transactions on Mobile Computing.

[13]  David Atienza,et al.  Prediction and management in energy harvested wireless sensor nodes , 2009, 2009 1st International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology.

[14]  Charles U. Martel,et al.  On non-preemptive scheduling of period and sporadic tasks , 1991, [1991] Proceedings Twelfth Real-Time Systems Symposium.

[15]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[16]  Hwee Pink Tan,et al.  Design and performance analysis of MAC schemes for Wireless Sensor Networks Powered by Ambient Energy Harvesting , 2011, Ad Hoc Networks.

[17]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

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