A Critical Analysis of Healthcare Applications Over Fog Computing Infrastructures

Over the last decade, the number of Internet of Things (IoT) smart devices has grown exponentially. In order to support the computational demand of real-time latency-sensitive applications in healthcare, a new paradigm named Fog Computing has emerged. Fog Computing is located closer to the IoT devices/sensors and is considered to be an extension of the Cloud Computing. In this paper, a hospital ward room is used as a case study, where the scenario is simulated using the iFogSim simulator, in order to evaluate and analyse its behaviour in terms of latency, network usage, cost of transmission, and power consumption. The results point out the possibility to enhance Quality of Service for patients and care givers by adding the Fog Computing layer to the current Cloud infrastructure.

[1]  Rongxing Lu,et al.  Towards power consumption-delay tradeoff by workload allocation in cloud-fog computing , 2015, 2015 IEEE International Conference on Communications (ICC).

[2]  Songqing Chen,et al.  FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation , 2015, 2015 IEEE International Conference on Networking, Architecture and Storage (NAS).

[3]  Mingzhe Jiang,et al.  Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction , 2015, 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing.

[4]  Rajkumar Buyya,et al.  iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments , 2016, Softw. Pract. Exp..

[5]  David S. Linthicum Connecting Fog and Cloud Computing , 2017, IEEE Cloud Computing.

[6]  Alex Reznik,et al.  Mobile Edge Cloud System: Architectures, Challenges, and Approaches , 2018, IEEE Systems Journal.

[7]  Arwa Alrawais,et al.  Fog Computing for the Internet of Things: Security and Privacy Issues , 2017, IEEE Internet Computing.

[8]  Ivan Stojmenovic,et al.  The Fog computing paradigm: Scenarios and security issues , 2014, 2014 Federated Conference on Computer Science and Information Systems.

[9]  Yong Xiang,et al.  Cost Efficient Resource Management in Fog Computing Supported Medical Cyber-Physical System , 2017, IEEE Transactions on Emerging Topics in Computing.

[10]  Hans-Ulrich Prokosch,et al.  A scoping review of cloud computing in healthcare , 2015, BMC Medical Informatics and Decision Making.

[11]  Dimitra I. Kaklamani,et al.  A Cooperative Fog Approach for Effective Workload Balancing , 2017, IEEE Cloud Computing.

[12]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[13]  Mario Nemirovsky,et al.  Key ingredients in an IoT recipe: Fog Computing, Cloud computing, and more Fog Computing , 2014, 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD).

[14]  Luis Rodero-Merino,et al.  Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing , 2014, CCRV.

[15]  Ning Ye,et al.  Private and Secured Medical Data Transmission and Analysis for Wireless Sensing Healthcare System , 2017, IEEE Transactions on Industrial Informatics.

[16]  Muhammad Murtaza Yousaf,et al.  Establishing the State of the Art Knowledge Domain of Cloud Computing , 2016 .

[17]  Ali A. Ghorbani,et al.  A Lightweight Privacy-Preserving Data Aggregation Scheme for Fog Computing-Enhanced IoT , 2017, IEEE Access.