Application Placement in Fog-Enabled Internet of Things (IoT) Healthcare System Using Body Sensor Networks

Introduction

Over the last two years the people across the globe has been facing a nobel coronavirus disease (COVID‐19) and pandemicity of this virus significantly disrupting various sector specifically healthcare services is mostly affected. Due to this covid-19 outbreak, many people suffering from different diseases like diabetics and cardiovascular patients staying in the home are regularly monitored through telephonic and video conferencing to break the covid-19 epidemic (Brogi, A.et al. 2017) (Gia, T. N. et al.2017). The shortage of nurses and beds leads to the development of various real-time health monitoring applications. The projected growth of wireless healthcare is expected to reach USD 337.55 billion by 2026. Similarly, in some other report released by Cisco, there are nearly 7.1 million patients are using connected medical devices, and the global wireless healthcare market is expected to reach USD110B by 2020. Healthcare IoT services put many stringent requirements to the service provider in terms resource utilization efficiency and bandwidth efficiency. The traditional computing paradigm solution is not able to satisfy the IoTusers’ requirements (Deng, S. et al. 2020). To combat the various issues like undesired latency, Quality of Service(QoS) parameters like average response time, deadline satisfaction ratio, accuracy, etc. various extension of cloud computing is proposed like Mobile Cloud Computing, Edge Computing, Fog Computing, Mist Computing and Serverless computing to meet the demand of large scale IoT applications e.g. Smart healthcare, Smart City, Intelligent Transport System, Virtual Reality and Augmented Reality application (Chang, C. et al.2017) (Alam, M. F.et al. 2017).The Internet of Things (IoT) is a revolutionary communication technology capable of connecting different physical things tothe network through different long-range and short-range communication protocols. The rapid development of IoT devices supporting various smart city applications with various applications is increasing at a very rapid rate. A recent report by different organizations like International Data Corporation(IDC) and Gartner Inc. projected that the growth rate of various types of sensors will increase 50 million by 2025 and correspondingly, the devices will be increasing in the range of 50 billion to 1 trillion. Due to this ever-growing number of IoT devices, it makes possible to connect 7.1 million patients using medical sensor devices attached to the human body to sense the physiological data continuously. The above growth of wireless healthcare products tends to the development of various smart healthcare IoT applications through which a patient can be monitored remotely. Each sensor device attached into the body is uniquely identified by the UID, or MAC, or IP connected to the gateway (Barik, R. K.et al.2018) (Aydin, M. E. et al.2004). The large number of sensor devices manufactured by different vendors are used in healthcare that results into high volume of data. To analyze, pre-processing and storing these large volume and varieties of IoT data cloud computing has been used earlier on a large scale. The IoT-Cloud paradigm was the only solution for healthcare IoT devices (Bajeh, A. O. et al. 2011). The sensor devices continuously sense and forward environmental and physiological data to the cloud server for execution and analysis. The IoT-Cloud paradigm enables on-demand network and computational resources like server, storage, application, and services that an IoT user can use with minimal effort and pay per use basis in different form like IaaS, PaaS, and SaaS. Despite these wonderful benefits, the desired (QoS) requirement of various real-time IoT applications cannot meet by the cloud service provider. The delay that occurred due to centralized processing of IoT tasks may lead to a serious problem if a patient is waiting for some result. The other limitations of cloud computing are low bandwidth, energy consumption, etc.. In recent years, smart healthcare has become an emerging IoT application (Baker, S. B.et al. 2017).A smart healthcare system consisting of various wearable sensors, body area networks, etc.,is used by medical professionals to monitor the status of health in real-time. Most importantly, smart healthcare and body sensor network assist early detection of disease and their safety provision. To meet the desired QoS requirement of various real-time IoT applications such as Intelligent Healthcare, Intelligent traffic monitoring, Smart Home, and with many more real-time applications in a smart city, the pioneer of networking system CISCO proposed Fog computing model to support the ultra-low latency requirement of various mission-critical IoT applications with various other characteristics like mobility support and geographical location support.