Quality of Service and Privacy in Internet of Things Dedicated to Healthcare

Abstract

The Internet of Things (IoT) based healthcare systems usually composed of medical and environmen- tal sensors, remote servers, and the network. These systems focus on providing remote monitoring, disease diagnosis, and treatment progress observation. The healthcare systems in IoT domain helps in realizing long-term economical, ubiquitous, and patient centered care systems, that result in improving treatment and patient outcomes. This research contributes to the domain by proposing a Cloud-Fog based architecture that can embrace multiple healthcare scenarios, and able to adapt dynamically with the context and status of the patients. It allows the mobility and physical activity of the patients in the environment through deployment and implementation of an appropriate Received Signal Strength (RSS) based handoff mechanism. It also proposes a mobility-aware task scheduling and allocation approach in cloud-fog computing paradigm, called MobMBAR, with the objective of reducing the total schedule time (makespan). MobMBAR performs dynamic balanced healthcare tasks distribution between the cloud and fog devices. It is a data locality based approach that depends on changing the location where the data is computed to where it actually resides. It takes scheduling decisions considering the priorities of tasks represented in their classifications and maximum response time. To evaluate the performance, we conduct an intensive simulation study with different stationery and mobility scenarios, and compare against other state of art solutions. We measure the performance metrics: makespan, network load, energy consumption, percentage of missed tasks, latency, execution cost, number of handoffs, and resource utilization, and study the effect of varying number of tasks, number of cloud devices, handoff threshold, and percentage of mobile devices on the performance metrics. The experiments show acceptable results in terms of makespan, miss ratio, cost, latency, and net- work load. In case of mobility support, it shows that missed tasks ratios doesn’t exceed one thou- sandths percent, and is proven to be 88% lower than state-of-the-art solutions in terms of makespan and 92% lower in terms of energy consumption. This research also includes a realistic simulation case study that uses the layout of an indoor hospital building in Chicago, and it has demonstrated accept- able performance. To authenticate and secure communication between IoT device and gateways, the thesis also proposes a DTLS (Datagram Transport Layer Security) based mobility-enabled authentica-