Zero Energy Network stack for Energy Harvested WSNs

We present our ``Zero Energy Network'' (ZEN) protocol stack for energy harvesting wireless sensor networks applications. The novelty in our work is $4$ fold: (1) Energy harvesting aware fully featured MAC layer. Carrier sensing, Backoff algorithms, ARQ, RTS/CTS mechanisms, Adaptive Duty Cycling are either auto configurable or available as tunable parameters to match the available energy (b) Energy harvesting aware Routing Protocol. The multi-hop network establishes routes to the base station using a modified version of AODVjr routing protocol assisted by energy predictions. (c) Application of a time series called ``Holt-Winters'' for predicting the incoming energy. (d) A distributed smart application running over the ZEN stack which utilizes a multi parameter optimized perturbation technique to optimally use the available energy. The application is capable of programming the ZEN stack in an energy efficient manner. The energy harvested distributed smart application runs on a realistic solar energy trace with a three year seasonality database. We implement a smart application, capable of modifying itself to suit its own as well as the network's energy level. Our analytical results show a close match with the measurements conducted over EHWSN testbed.

[1]  Dusit Niyato,et al.  Sleep and Wakeup Strategies in Solar-Powered Wireless Sensor/Mesh Networks: Performance Analysis and Optimization , 2007, IEEE Transactions on Mobile Computing.

[2]  Philip Levis,et al.  The β-factor: measuring wireless link burstiness , 2008, SenSys '08.

[3]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.

[4]  Luca Benini,et al.  Adaptive Power Management for Environmentally Powered Systems , 2010, IEEE Transactions on Computers.

[5]  Pai H. Chou,et al.  AmbiMax: Autonomous Energy Harvesting Platform for Multi-Supply Wireless Sensor Nodes , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[6]  Xiao-dong Zhang,et al.  A study of short term forecasting of the railway freight volume in China using ARIMA and Holt-Winters models , 2010, 2010 8th International Conference on Supply Chain Management and Information.

[7]  Wei Guan,et al.  A Kind of Demand Forecasting Model Based on Holt-Winters Model and Customer-credit Evaluation Model , 2006, 2006 International Conference on Service Systems and Service Management.

[8]  Fenghui Zhang,et al.  A Routing Algorithm for ZigBee Network Based on Dynamic Energy Consumption Decisive Path , 2009, 2009 International Conference on Computational Intelligence and Natural Computing.

[9]  Ian D. Chakeres,et al.  AODVjr, AODV simplified , 2002, MOCO.

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

[11]  Babak Hossein Khalaj,et al.  Delay-constrained utility maximisation in multi-hop random access networks , 2010, IET Commun..

[12]  Hanif D. Sherali,et al.  Linear Programming and Network Flows , 1977 .

[13]  Wenjing Lou,et al.  Energy-aware geographic routing in lossy wireless sensor networks with environmental energy supply , 2006, QShine '06.

[14]  Lothar Thiele,et al.  Analysis, Comparison, and Optimization of Routing Protocols for Energy Harvesting Wireless Sensor Networks , 2010, 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing.

[15]  S. Kim,et al.  Trio: enabling sustainable and scalable outdoor wireless sensor network deployments , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[16]  Dimitri Marinakis,et al.  Scheduling recurring tasks in energy harvesting sensors , 2011, 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[17]  Mani B. Srivastava,et al.  Power management in energy harvesting sensor networks , 2007, TECS.

[18]  David E. Culler,et al.  Perpetual environmentally powered sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[19]  Mirco Musolesi.  Questions and Comments Cis6930 Presentation Pertaining to Publication: Mirco Musolesi , Cecilia Mascolo, Designing Mobility Models Based on Social Network Theory, Acm Sigmobile Mobile Computing and Communications Review , 2009 .

[20]  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.

[21]  Chandra R. Murthy,et al.  Power Management and Data Rate Maximization in Wireless Energy Harvesting Sensors , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[22]  David E. Culler,et al.  Trio: enabling sustainable and scalable outdoor wireless sensor network deployments , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[23]  P. Levis,et al.  BoX-MACs : Exploiting Physical and Link Layer Boundaries in Low-Power Networking , 2007 .

[24]  Chandra R. Murthy.  Power management and data rate maximization in wireless Energy Harvesting Sensors , 2008, PIMRC.

[25]  R. Srikant,et al.  Asymptotically Optimal Energy-Aware Routing for Multihop Wireless Networks With Renewable Energy Sources , 2007, IEEE/ACM Transactions on Networking.

[26]  Andrew G. Barto,et al.  Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks , 2007, 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[27]  Bao Rong Chang.  Forecasting short-term stock price indexes - an integrated predictor vs. neural network predictor , 2002, 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. TENCOM '02. Proceedings..