**5. Conclusions**

For the provision of services to elderly patients, patients with disabilities, and patients residing in remote or rural localities, where frequent access to hospitals is not an easy task, the healthcare applications providing remote medical facilities are getting popular expeditiously. Mostly, the applications providing remote medical services are deployed using cloud architecture because the cloud paradigm provides plentiful resources for the execution and analysis of medical data involved in the procedure of such applications. Due to the reliance of human lives on such applications, these applications require real-time processing of medical information with minimum delay. Owing to centralized architecture, the cloud computing paradigm lacks the provision of real-time services to end users when such applications are deployed on large scale. On the contrary, the fog paradigm offers computational services adjacent to the network edge by distributing resource-constraint fog devices throughout the network. This chapter presents a remote pain monitoring system based on a fog computing paradigm that senses and processes the biopotential signals of remotely situated patients to detect pain. Furthermore, the designed application offers remote access to patient health-related information through a web platform for the rapid provision of medical facilitation to the patient. To evaluate the proposed fog computing-based design with the traditional cloud computing-based application, several scenarios are created and executed on multiple scales using the iFogSim toolkit. The outcomes of the simulations validate the effectiveness of the proposed design in the provision of services with minimized delay. Furthermore, the proposed design offers reduced execution costs at cloud and network load as compared to the cloud computing-based design.
