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Resilient Wireless Sensor Networks

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This Springer Brief introduces wireless sensor networks (WSNs) and the need for resilient WSN operations in application domains. It presents traditional approaches of providing resilient operation of WSNs to ensure continuity of data delivery even when some network sensors fail.   The pros and cons of each these approaches are discussed.  Also included is an overview of network coding basics, and motivate the use of network coding-based protection in order to combine the advantages, but avoid the disadvantages of the traditional approaches.

The authors cover the design and analysis of a centralized approach to network coding-based protection of WSNs.  The coverage also includes practical and realistic network situations, and the coding strategies employed. Next discussed is how to recover from data losses using a distributed approach, which is more practical for large scale WSNs.   Algorithms for scheduling of transmissions while implementing network coding-based in the two cases of using digital network coding, and analog network coding are covered. 

Resilient Wireless Sensor Networks includes a concise, but an in-depth coverage of the use of network coding to implement  agile and resource efficient protection in WSNs.  It will be of  interest to professionals and researchers working in the areas of fault tolerance, network coding, and deployment of WSNs in harsh environment. Advanced-level students in electrical engineering and computer science will also find this research valuable as a reference.

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This Springer Brief introduces wireless sensor networks (WSNs) and the need for resilient WSN operations in application domains. It presents traditional approaches of providing resilient operation of WSNs to ensure continuity of data delivery even when some network sensors fail.   The pros and cons of each these approaches are discussed.  Also included is an overview of network coding basics, and motivate the use of network coding-based protection in order to combine the advantages, but avoid the disadvantages of the traditional approaches.
The authors cover the design and analysis of a centralized approach to network coding-based protection of WSNs.  The coverage also includes practical and realistic network situations, and the coding strategies employed. Next discussed is how to recover from data losses using a distributed approach, which is more practical for large scale WSNs.   Algorithms for scheduling of transmissions while implementing network coding-based in the two cases of using digital network coding, and analog network coding are covered. 
Resilient Wireless Sensor Networks includes a concise, but an in-depth coverage of the use of network coding to implement  agile and resource efficient protection in WSNs.  It will be of  interest to professionals and researchers working in the areas of fault tolerance, network coding, and deployment of WSNs in harsh environment. Advanced-level students in electrical engineering and computer science will also find this research valuable as a reference.

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