LiveWSN: A memory-efficient, energy-efficient, reprogrammable, and fault-tolerant platform for wireless sensor network

Memory optimization, energy conservation, over-the-air reprogramming, and fault tolerance are the critical challenges for the proliferation of the wireless sensor network. To address these challenges, a new wireless sensor network platform termed LiveWSN is presented in this article. In LiveWSN, several new design concepts are implemented, such as the hierarchical shared-stack scheduling and the pre-linking native-code reprogramming. By doing so, the data memory cost of the LiveWSN scheduling system can be optimized by 25% if compared with that of the traditional multithreaded MANTIS OS. Moreover, the application reprogramming code size can be decreased by 72.6% if compared with that of the Contiki dynamic-linking reprogramming. In addition to the new design concepts, the new research approach which addresses the energy conservation and fault tolerance challenges by combining the software technique and the multi-core hardware technique is applied in LiveWSN. By means of the multi-core hardware infrastructure, the lifetime of the LiveWSN nodes can be prolonged by 34% if compared with the single-core Live node. Moreover, the fault-tolerant performance of the wireless sensor network node can be optimized significantly. With the above features, LiveWSN becomes memory efficient, energy efficient, reprogrammable, and fault tolerant, and it can run on the high resource-constrained nodes to execute the outdoor real-time wireless sensor network applications.

[1]  Prasenjit Chanak,et al.  Energy efficient fault-tolerant multipath routing scheme for wireless sensor networks , 2013 .

[2]  Tossaporn Srisooksai,et al.  Practical data compression in wireless sensor networks: A survey , 2012, J. Netw. Comput. Appl..

[3]  Eric A. Brewer,et al.  USENIX Association Proceedings of HotOS IX : The 9 th Workshop on Hot Topics in Operating Systems , 2003 .

[4]  Adam Dunkels,et al.  Run-time dynamic linking for reprogramming wireless sensor networks , 2006, SenSys '06.

[5]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[6]  Rance Cleaveland,et al.  Using formal specifications to support testing , 2009, CSUR.

[7]  John K. Ousterhout,et al.  Why Threads Are A Bad Idea , 2013 .

[8]  Nitin Gupta,et al.  Wireless Sensor Network: A Review on Data Aggregation , 2011 .

[9]  Peter I. Corke,et al.  Darjeeling, a feature-rich VM for the resource poor , 2009, SenSys '09.

[10]  Hongling Shi,et al.  Development of an energy efficient, robust and modular multicore wireless sensor network , 2014 .

[11]  Amol Deshpande,et al.  Online Filtering, Smoothing and Probabilistic Modeling of Streaming data , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[12]  Maghsoud Abbaspour,et al.  An adaptive CSMA/TDMA hybrid MAC for energy and throughput improvement of wireless sensor networks , 2013, Ad Hoc Networks.

[13]  Mohamed F. Younis,et al.  Topology management techniques for tolerating node failures in wireless sensor networks: A survey , 2014, Comput. Networks.

[14]  Anurag Agarwal,et al.  The Internet of Things—A survey of topics and trends , 2014, Information Systems Frontiers.

[15]  Imrich Chlamtac,et al.  Internet of things: Vision, applications and research challenges , 2012, Ad Hoc Networks.

[16]  Dimitrios D. Vergados,et al.  Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[17]  Jeff Rose,et al.  MANTIS OS: An Embedded Multithreaded Operating System for Wireless Micro Sensor Platforms , 2005, Mob. Networks Appl..

[18]  Fernando J. Velez,et al.  Survey on the Characterization and Classification of Wireless Sensor Network Applications , 2014, IEEE Communications Surveys & Tutorials.

[19]  Jean-Pierre Chanet,et al.  LiveNode: LIMOS versatile embedded wireless sensor node , 2007 .

[20]  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.

[21]  Qiang Wang,et al.  Reprogramming wireless sensor networks: challenges and approaches , 2006, IEEE Network.

[22]  Y. Ahmet Sekercioglu,et al.  A Survey on Distributed Topology Control Techniques for Extending the Lifetime of Battery Powered Wireless Sensor Networks , 2013, IEEE Communications Surveys & Tutorials.