Lakhan Abdullah, Sodhro Ali Hassan, Majumdar Arnab, Khuwuthyakorn Pattaraporn, Thinnukool Orawit
Department of Computer Science, Dawood University of Engineering and Technology, Karachi 74800, Pakistan.
College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China.
Sensors (Basel). 2022 Mar 19;22(6):2379. doi: 10.3390/s22062379.
Mobile-cloud-based healthcare applications are increasingly growing in practice. For instance, healthcare, transport, and shopping applications are designed on the basis of the mobile cloud. For executing mobile-cloud applications, offloading and scheduling are fundamental mechanisms. However, mobile healthcare workflow applications with these methods are widely ignored, demanding applications in various aspects for healthcare monitoring, live healthcare service, and biomedical firms. However, these offloading and scheduling schemes do not consider the workflow applications' execution in their models. This paper develops a lightweight secure efficient offloading scheduling (LSEOS) metaheuristic model. LSEOS consists of light weight, and secure offloading and scheduling methods whose execution offloading delay is less than that of existing methods. The objective of LSEOS is to run workflow applications on other nodes and minimize the delay and security risk in the system. The metaheuristic LSEOS consists of the following components: adaptive deadlines, sorting, and scheduling with neighborhood search schemes. Compared to current strategies for delay and security validation in a model, computational results revealed that the LSEOS outperformed all available offloading and scheduling methods for process applications by 10% security ratio and by 29% regarding delays.
基于移动云的医疗保健应用在实践中日益增多。例如，医疗保健、交通和购物应用都是基于移动云设计的。对于执行移动云应用而言，卸载和调度是基本机制。然而，采用这些方法的移动医疗工作流应用却被广泛忽视，而医疗保健监测、实时医疗服务和生物医学公司在各个方面都需要此类应用。然而，这些卸载和调度方案在其模型中并未考虑工作流应用的执行情况。本文开发了一种轻量级安全高效卸载调度（LSEOS）元启发式模型。LSEOS由轻量级、安全的卸载和调度方法组成，其执行卸载延迟小于现有方法。LSEOS的目标是在其他节点上运行工作流应用，并将系统中的延迟和安全风险降至最低。元启发式LSEOS由以下组件组成：自适应期限、排序以及采用邻域搜索方案进行调度。与当前模型中用于延迟和安全验证的策略相比，计算结果表明，LSEOS在安全率方面比所有可用的流程应用卸载和调度方法高出10%，在延迟方面高出29%。
