Energetic sustainability of routing algorithms for energy-harvesting wireless sensor networks

A new class of wireless sensor networks that harvest power from the environment is emerging because of its intrinsic capability of providing unbounded lifetime. While a lot of research has been focused on energy-aware routing schemes tailored to battery-operated networks, the problem of optimal routing for energy harvesting wireless sensor networks (EH-WSNs) has never been explored. The objective of routing optimization in this context is not extending network lifetime, but maximizing the workload that can be autonomously sustained by the network. In this work we present a methodology for assessing the energy efficiency of routing algorithms for networks whose nodes drain power from the environment. We first introduce the energetic sustainability problem, then we define the maximum energetically sustainable workload (MESW) as the objective function to be used to drive the optimization of routing algorithms for EH-WSNs. We propose a methodology that makes use of graph algorithms and network simulations for evaluating the MESW starting from a network topology, a routing algorithm and a distribution of the environmental power available at each node. We present a tool flow implementing the proposed methodology and we show comparative results achieved on several routing algorithms. Experimental results highlight that routing strategies that do not take into account environmental power do not provide optimal results in terms of workload sustainability. Using optimal routing algorithms may lead to sizeable enhancements of the maximum sustainable workload. Moreover, optimality strongly depends on environmental power configurations. Since environmental power sources change over time, our results prompt for a new class of routing algorithms for EH-WSNs that are able to dynamically adapt to time-varying environmental conditions.

[1]  Jan M. Rabaey,et al.  Energy aware routing for low energy ad hoc sensor networks , 2002, 2002 IEEE Wireless Communications and Networking Conference Record. WCNC 2002 (Cat. No.02TH8609).

[2]  Mani B. Srivastava,et al.  Design considerations for solar energy harvesting wireless embedded systems , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[3]  Adam Dunkels,et al.  Solar-aware clustering in wireless sensor networks , 2004, Proceedings. ISCC 2004. Ninth International Symposium on Computers And Communications (IEEE Cat. No.04TH8769).

[4]  Hartmut Ritter,et al.  Utilizing solar power in wireless sensor networks , 2003, 28th Annual IEEE International Conference on Local Computer Networks, 2003. LCN '03. Proceedings..

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

[6]  Robert Cole,et al.  Computer Communications , 1982, Springer New York.

[7]  Catherine Rosenberg,et al.  Energy and Cost Optimizations in Wireless Sensor Networks: A Survey , 2005 .

[8]  Mani Srivastava,et al.  Distributed Energy Harvesting for Energy Neutral Sensor Networks , 2005 .

[9]  Mohamed F. Younis,et al.  A survey on routing protocols for wireless sensor networks , 2005, Ad Hoc Networks.

[10]  Anantha Chandrakasan,et al.  DSPs for energy harvesting sensors: applications and architectures , 2005, IEEE Pervasive Computing.

[11]  Deborah Estrin,et al.  Directed diffusion for wireless sensor networking , 2003, TNET.

[12]  Leandros Tassiulas,et al.  Routing for Maximum System Lifetime in Wireless Ad-hoc Networks , 1999 .

[13]  A. Varga,et al.  THE OMNET++ DISCRETE EVENT SIMULATION SYSTEM , 2003 .

[14]  Nathan Ickes,et al.  Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks , 2001, MobiCom '01.

[15]  Anantha Chandrakasan,et al.  Bounding the lifetime of sensor networks via optimal role assignments , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[16]  Joseph A. Paradiso,et al.  Energy scavenging for mobile and wireless electronics , 2005, IEEE Pervasive Computing.

[17]  Nael B. Abu-Ghazaleh,et al.  A taxonomy of wireless micro-sensor network models , 2002, MOCO.

[18]  Andrea Acquaviva,et al.  Energetic sustainability of environmentally powered wireless sensor networks , 2006, PE-WASUN '06.

[19]  Pekka Orponen,et al.  Exact and approximate balanced data gathering in energy-constrained sensor networks , 2005, Theor. Comput. Sci..

[20]  Mani Srivastava,et al.  Energy Harvesting Aware Power Management , 2005 .