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A Secure Fog Computing Architecture for Continuous Health Monitoring

  • Sanjivani Deokar
  • Monika Mangla
  • Rakhi Akhare
Chapter
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Part of the Signals and Communication Technology book series (SCT)

Abstract

Automation of health monitoring has witnessed an unmatched transformation during the past decade owing to advancement in the IoT. In automated health monitoring system, patient is efficiently and precisely monitored using numerous sensing devices. These monitored parameters need to be forwarded and processed at cloud which aids medical expert in diagnosis and treatment. However, the transmission of this data to cloud necessitates a wide bandwidth and high speed networks as real-time monitoring generates a plethora of data. In order to address this issue, the computing resources are pushed to the edges of the network, known as fog computing. Fog computing eliminates the limitations of cloud computing as it has low bandwidth requirement and reduced latency time. Additionally, it also addresses the issue of scalability and thus caters to the demand of IoT-based computing environment further making it an appropriate choice for implementing any latency-sensitive and location-sensitive application, e.g., automated Health Monitoring System (HMS). In this chapter, the authors discuss the evolution in IoT, concept of cloud computing and related issues. Thereafter, the authors present the concept of fog computing along with associated constraints and challenges. Furthermore, the authors propose a secure fog computing architecture by integrating security aspect in the fog layer. In the proposed architecture, authors present two-step approach to maintain privacy and integrity of health data. The proposed architecture caters the demand of a secure automated HMS that advocates its widespread deployment in real life.

Keywords

IoT Cloud computing Fog computing Healthcare automation Sensors Edge devices Data security Data Privacy 

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Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Sanjivani Deokar
    • 1
  • Monika Mangla
    • 1
  • Rakhi Akhare
    • 1
  1. 1.CSED, LTCENavi MumbaiIndia

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