Next-generation cloudlet federation for Internet of Things in healthcare: Enhancing response time and energy efficiency

Abstract

The integration of the Internet of Things (IoT) with edge computing has revolutionized various sectors, including healthcare, by enabling timely patient monitoring and service availability. These services encompass emergency responses, regular treatment, and physician assistance. Healthcare systems leverage mobile edge computing, fog computing, and cloudlet computing to offload data and computations and minimize delays and energy consumption. However, edge computing solutions face limitations such as restricted area coverage, diverse service requirements, and insufficient computational power, making them unsuitable for large-scale data processing and computation. To address the growing need for seamless patient information sharing among doctors and specialists across different hospitals, a resource-sharing solution, such as the cloudlet federation, is essential. Nonetheless, integrating IoT systems with cloudlet federations in healthcare presents challenges, primarily because of the necessity for mobile nodes such as ambulances, in addition to the fixed-edge nodes and brokers typical of traditional cloudlet federations. This study proposes a modified cloudlet federation model designed to overcome these challenges by effectively managing data from heterogeneous nodes. Our approach enhanced response times, reduced energy consumption, and ensured the availability of comprehensive patient information. The experimental results demonstrate a 49% improvement in response time and a 51% reduction in energy consumption compared with existing cloud-based solutions.