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Cloud-assisted body area networks: state-of-the-art and future challenges

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Abstract

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

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Authors and Affiliations

  1. DIMES, University of Calabria, 87036, Rende, CS, Italy

    Giancarlo Fortino

  2. SSE, The University of Reading, Reading, RG6 6AX, UK

    Giuseppe Di Fatta

  3. Telstra Corporation Limited, Melbourne, Australia

    Mukaddim Pathan

  4. National Technical University of Athens, Athens, Greece

    Athanasios V. Vasilakos

Authors
  1. Giancarlo Fortino
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  2. Giuseppe Di Fatta
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  3. Mukaddim Pathan
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  4. Athanasios V. Vasilakos
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Correspondence to Giancarlo Fortino.

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Fortino, G., Di Fatta, G., Pathan, M. et al. Cloud-assisted body area networks: state-of-the-art and future challenges. Wireless Netw 20, 1925–1938 (2014). https://doi.org/10.1007/s11276-014-0714-1

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