A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT
Tekijät: Azimi I, Anzanpour A, Rahmani AM, Pahikkala T, Levorato M, Liljeberg P, Dutt N
Kustantaja: ASSOC COMPUTING MACHINERY
Julkaisuvuosi: 2017
Journal: ACM Transactions in Embedded Computing Systems
Tietokannassa oleva lehden nimi: ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS
Lehden akronyymi: ACM T EMBED COMPUT S
Artikkelin numero: ARTN 174
Vuosikerta: 16
Numero: Suppl. 5 (SI)
Sivujen määrä: 20
ISSN: 1539-9087
eISSN: 1558-3465
DOI: https://doi.org/10.1145/3126501
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/28258783
The Internet of Things (IoT) paradigm holds significant promises for remote health monitoring systems. Due to their life-or mission-critical nature, these systems need to provide a high level of availability and accuracy. On the one hand, centralized cloud-based IoT systems lack reliability, punctuality and availability (e.g., in case of slow or unreliable Internet connection), and on the other hand, fully outsourcing data analytics to the edge of the network can result in diminished level of accuracy and adaptability due to the limited computational capacity in edge nodes. In this paper, we tackle these issues by proposing a hierarchical computing architecture, HiCH, for IoT-based health monitoring systems. The core components of the proposed system are 1) a novel computing architecture suitable for hierarchical partitioning and execution of machine learning based data analytics, 2) a closed-loop management technique capable of autonomous system adjustments with respect to patient's condition. HiCH benefits from the features offered by both fog and cloud computing and introduces a tailored management methodology for healthcare IoT systems. We demonstrate the efficacy of HiCH via a comprehensive performance assessment and evaluation on a continuous remote health monitoring case study focusing on arrhythmia detection for patients suffering from CardioVascular Diseases (CVDs).
Ladattava julkaisu This is an electronic reprint of the original article. |  |
