Abstract
Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.
Highlights
The use of digital mobile applications in practice to deal with different life activities, e.g., digital shopping, digital booking, digital healthcare, etc., is growing
To solve the joint application partitioning and task-scheduling problem, we propose the Dynamic Application-Partitioning Workload Task-Scheduling Secure (DAPWTS) framework, consisting of different phases, such as the secure min-cut, task-sequencing phase, task-scheduling phase, and failure-aware scheduling phase
To deal with the problem, we devised a dynamic application-partitioning task scheduling (DAPWTS) framework, which consists of the following components: (i) Applicationpartitioning component; (ii) Task-sequencing component; (iii) Task-scheduling component; (iv) Failure-aware task scheduling of the mobile workflow in the proposed architecture
Summary
The use of digital mobile applications in practice to deal with different life activities, e.g., digital shopping, digital booking, digital healthcare, etc., is growing. These applications have distributed runtime such as JAVA JVM for execution on different platforms, known as application partitioning. In recent years, emerging technologies such as edge computing and wireless networks for digital healthcare applications have been widely used for applications. The primary goal of this study was to undertake encryption and decryption on the local machine to ensure the security of data before offloading to the edge-cloud network. Existing studies have widely ignored local device energy and resource consumption during the implementation of security schemes at the local machine. Existing studies have widely missed the deadline constraints of applications in the application-partitioning problem
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