FogCom:SDN-enabled fog node selection for early detection of communicable diseases

• Published in: Journal of King Saud University. Computer and information sciences Vol. 35; no. 6; p. 101432
• Main Authors: Sarkar, Joy Lal, Cowlessur, Sanjeev K., Ramasamy, V., Pati, Bibudhendu, Mahesh Selvi, T., Panigrahi, Chhabi Rani, Majumder, Bibek, Verma, Rajesh Kumar, Fasech Qureshi, Nawab Muhammad
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2023; Elsevier
• Subjects: CNN; Communicable diseases; Fog node; SDN; WBAN; WBAN; CNN; Fog node; SDN; Communicable diseases
• ISSN: 1319-1578; 2213-1248
• DOI: 10.1016/j.jksuci.2022.10.023

A communicable illness is one that spreads from person to person by a number of means, including contact with blood and body fluids, inhaling an airborne virus, or being bitten by an insect. Internet of Things (IoT)-oriented medical technologies have proliferated in prior decades, and many more applications depend on wearable sensors for versatility. Modern research has examined the use of software-defined networking (SDN)-oriented fog framework to create intelligent health care services. To choose the best fog nodes within the fog layers, however, to anticipate communicable disease detection.To solve this issue, the SDN-enabled Fog Node Selection for Early Detection of Communicable Diseases (FogCom) is created in this study. The FogCom picks the optimal fog nodes using game theory’s Subgame Perfect Nash Equilibrium (SPNE) method. The suggested method also takes into account the three-layered CNN methodology for detecting communicable illnesses. Efficiency analysis shows that the suggested FogCom outperforms earlier baseline techniques.