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Sensors 2014, 14(3), 4806-4830; doi:10.3390/s140304806

A Cloud-Assisted Random Linear Network Coding Medium Access Control Protocol for Healthcare Applications

1,* , 2
1 Department of Signal Theory and Communications (TSC), Technical University of Catalonia (UPC—BarcelonaTECH), C./ Esteve Terradas 7, C4-202P, Castelldefels 08860, Spain 2 Telecommunications Technological Centre of Catalonia (CTTC), Castelldefels 08860, Spain
* Author to whom correspondence should be addressed.
Received: 20 January 2014 / Revised: 26 February 2014 / Accepted: 5 March 2014 / Published: 10 March 2014
(This article belongs to the Special Issue Sensors Data Fusion for Healthcare)
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Relay sensor networks are often employed in end-to-end healthcare applications to facilitate the information flow between patient worn sensors and the medical data center. Medium access control (MAC) protocols, based on random linear network coding (RLNC), are a novel and suitable approach to efficiently handle data dissemination. However, several challenges arise, such as additional delays introduced by the intermediate relay nodes and decoding failures, due to channel errors. In this paper, we tackle these issues by adopting a cloud architecture where the set of relays is connected to a coordinating entity, called cloud manager. We propose a cloud-assisted RLNC-based MAC protocol (CLNC-MAC) and develop a mathematical model for the calculation of the key performance metrics, namely the system throughput, the mean completion time for data delivery and the energy efficiency. We show the importance of central coordination in fully exploiting the gain of RLNC under error-prone channels.
Keywords: MAC protocol design; network coding; cloud; WBANs; WSNs; healthcare MAC protocol design; network coding; cloud; WBANs; WSNs; healthcare
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Kartsakli, E.; Antonopoulos, A.; Alonso, L.; Verikoukis, C. A Cloud-Assisted Random Linear Network Coding Medium Access Control Protocol for Healthcare Applications. Sensors 2014, 14, 4806-4830.

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