, Volume 7, Issue 2, pp 439–441 | Cite as

Personalized Health Tracking with Edge Computing Technologies

  • Salvatore Distefano
  • Dario Bruneo
  • Francesco Longo
  • Giovanni Merlino
  • Antonio Puliafito


The health monitoring component is the essential block, a pillar of several e-health systems. Plenty of health tracking applications and specific technologies such as smart devices, wearables, and data management systems are available. To be effective, promptly reacting to issues, a health monitoring service must ensure short delays in data sensing, collection, and processing activities. This is an open problem that distributed computing paradigms, such as Internet of Things (IoT), Cloud, and Edge computing, could address. The solution proposed in this paper is based on Stack4Things, an IoT-Cloud framework to manage edge nodes such as mobiles, smart objects, network devices, workstations, as a whole, a computing infrastructure allowing to provide resources on-demand, as services, to end users. Through Stack4Things facilities, the health tracking system can locate the closer computing resource to offload processing and thus reducing latency per the Edge computing paradigm.


Health monitoring IoT Cloud Edge computing Stack4Things 


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Social and Urban Computing GroupKazan Federal UniversityKazanRussia
  2. 2.Mobile and Distributed Systems Laboratory (MDSLAB)University of MessinaMessinaItaly

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