Energy-aware routing for biomedical wireless sensor networks

Available wireless sensor networks targeting the domain of healthcare enables the development of new applications and services in the context of E-Health. Such networks play an important role in several scenarios of patient monitoring, particularly those where data collection is vital for diagnosis and/or research purposes. However, despite emerging solutions, wearable sensors still depend on users' acceptance. One proposed solution to improve wearability relies on the use of smaller sensing nodes, requiring more energy-efficient networks, due to smaller room available for energy sources. In such context, smaller wireless sensor network nodes are required to work long time periods without human intervention and, at the same time, to provide appropriate levels of reliability and quality of service. Satisfaction of these two goals depends on several key factors, such as the routing protocol, the network topology, and energy efficiency. This paper offers a solution to increase the network lifetime based on a new Energy-Aware Objective Function used to design a Routing Protocol for Low-Power and Lossy Networks. The proposed Objective Function uses the Expected Transmission Count Metric and the Remaining Energy on each sensor node to compute the best paths to route data packets across the network. When compared with state of the art solutions, the proposed method increases the network lifetime by 21% and reduces the peaks of energy consumption by 12%. In this way, wireless sensor network nodes wearability can be improved, making them smaller and lighter, while maintaining the required performance.

[1]  Paulo Mendes,et al.  Framework for QoS Performance Assessment on Biomedical Wireless Sensor Networks , 2012, BIODEVICES.

[2]  L. Oberg,et al.  A Complete Energy Dissipation Model forWireless Sensor Networks , 2007, 2007 International Conference on Sensor Technologies and Applications (SENSORCOMM 2007).

[3]  Chun-Chieh Hsiao,et al.  A H-QoS-demand personalized home physiological monitoring system over a wireless multi-hop relay network for mobile home healthcare applications , 2009, J. Netw. Comput. Appl..

[4]  Ian F. Akyildiz,et al.  Wireless multimedia sensor networks: A survey , 2007, IEEE Wireless Communications.

[5]  Kemal Bicakci,et al.  Prolonging network lifetime with multi-domain cooperation strategies in wireless sensor networks , 2010, Ad Hoc Networks.

[6]  Nei Kato,et al.  Extending the lifetime of wireless sensor networks: A hybrid routing algorithm , 2012, Comput. Commun..

[7]  Jean-Philippe Vasseur,et al.  Interconnecting Smart Objects with IP: The Next Internet , 2010 .

[8]  Sajal K. Das,et al.  EBRP: Energy-Balanced Routing Protocol for Data Gathering in Wireless Sensor Networks , 2011, IEEE Transactions on Parallel and Distributed Systems.

[9]  Dengfeng Yang,et al.  QoS Provision for Wireless Sensor Networks , 2009 .

[10]  Nikolaos Preve Ubiquitous Healthcare Computing with Sensor Grid Enhancement with Data Management System (SEGEDMA) , 2009, Journal of Medical Systems.

[11]  Siarhei Kuryla,et al.  RPL: IPv6 Routing Protocol for Low power and Lossy Networks , 2010 .

[12]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[13]  JeongGil Ko,et al.  Evaluating the Performance of RPL and 6LoWPAN in TinyOS , 2011 .

[14]  Antonella Molinaro,et al.  From MANET To IETF ROLL Standardization: A Paradigm Shift in WSN Routing Protocols , 2011, IEEE Communications Surveys & Tutorials.

[15]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2005, Wirel. Networks.

[16]  Ming Tao,et al.  An Adaptive Energy-aware Multi-path Routing Protocol with Load Balance for Wireless Sensor Networks , 2012, Wirel. Pers. Commun..

[17]  Qing Zhao,et al.  On the lifetime of wireless sensor networks , 2005, IEEE Communications Letters.

[18]  Tao Liu,et al.  An energy-balancing clustering approach for gradient-based routing in wireless sensor networks , 2012, Comput. Commun..

[19]  Huei-Wen Ferng,et al.  Energy-Efficient Routing Protocol for Wireless Sensor Networks with Static Clustering and Dynamic Structure , 2011, Wireless Personal Communications.

[20]  Soundar R. T. Kumara,et al.  Distributed energy balanced routing for wireless sensor networks , 2009, Comput. Ind. Eng..

[21]  Philip Levis,et al.  The Minimum Rank with Hysteresis Objective Function , 2012, RFC.

[22]  Adam Dunkels,et al.  Software-based sensor node energy estimation , 2007, SenSys '07.

[23]  Adam Dunkels,et al.  Low-power wireless IPv6 routing with ContikiRPL , 2010, IPSN '10.

[24]  Pascal Thubert,et al.  Compression Format for IPv6 Datagrams over IEEE 802.15.4-Based Networks , 2011, RFC.

[25]  Dominique Barthel,et al.  Routing Metrics Used for Path Calculation in Low-Power and Lossy Networks , 2012, RFC.

[26]  Adam Dunkels,et al.  Demo abstract: Software-based sensor node energy estimation , 2007 .

[27]  JeongGil Ko,et al.  ContikiRPL and TinyRPL: Happy Together , 2011 .

[28]  L. A. Grieco,et al.  Performance analysis of the RPL Routing Protocol , 2011, 2011 IEEE International Conference on Mechatronics.

[29]  JeongGil Ko,et al.  The Trickle Algorithm , 2011, RFC.

[30]  Adam Dunkels,et al.  Cross-Level Sensor Network Simulation with COOJA , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[31]  Pascal Thubert,et al.  Objective Function Zero for the Routing Protocol for Low-Power and Lossy Networks (RPL) , 2012, RFC.

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

[33]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[34]  JeongGil Ko,et al.  Connecting low-power and lossy networks to the internet , 2011, IEEE Communications Magazine.

[35]  Adam Dunkels,et al.  Poster Abstract: Low-Power Wireless IPv6 Routing with ContikiRPL , 2010, IPSN 2010.

[36]  Bechir Hamdaoui,et al.  A Survey on Energy-Efficient Routing Techniques with QoS Assurances for Wireless Multimedia Sensor Networks , 2012, IEEE Communications Surveys & Tutorials.

[37]  Yacine Challal,et al.  Wireless sensor networks for rehabilitation applications: Challenges and opportunities , 2013, J. Netw. Comput. Appl..

[38]  Mohamed F. Younis,et al.  Strategies and techniques for node placement in wireless sensor networks: A survey , 2008, Ad Hoc Networks.

[39]  Soundar R. T. Kumara,et al.  Distributed routing in wireless sensor networks using energy welfare metric , 2010, Inf. Sci..

[40]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[41]  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).