Akram Aasma, Anjum Fatima, Latif Sajid, Zulfiqar Muhammad Imran, Nazir Mohsin
Department of Computer Science, Lahore College for Women University, Lahore, Punjab, Pakistan.
Department of Computer Science, University of Arid Agriculture Rawalpindi, Rawalpindi, Punjab, Pakistan.
PeerJ Comput Sci. 2024 Nov 19;10:e2484. doi: 10.7717/peerj-cs.2484. eCollection 2024.
The Internet of Things (IoT) paradigm is a foundational and integral factor for the development of smart applications in different sectors. These applications are comprised over set of interconnected modules that exchange data and realize the distributed data flow (DDF) model. The execution of these modules on distant cloud data-center is prone to quality of service (QoS) degradation. This is where fog computing philosophy comes in to bridge this gap and bring the computation closer to the IoT devices. However, resource management in fog and optimal allocation of fog devices to application modules is critical for better resource utilization and achieve QoS. Significant challenge in this regard is to manage the fog network dynamically to determine cost effective placement of application modules on resources. In this study, we propose the optimal placement strategy for smart health-care application modules on fog resources. The objective of this strategy is to ensure optimal execution in terms of latency, bandwidth and earliest completion time as compared to few baseline techniques. A honey bee inspired strategy has been proposed for allocation and utilization of the resource for application module processing. In order to model the application and measure the effectiveness of our strategy, iFogSim Java-based simulation classes have been extended and conduct the experiments that demonstrate the satisfactory results.
物联网（IoT）范式是不同领域智能应用发展的基础和不可或缺的因素。这些应用由一组相互连接的模块组成，这些模块交换数据并实现分布式数据流（DDF）模型。在远程云数据中心执行这些模块容易导致服务质量（QoS）下降。在此背景下，雾计算理念应运而生，以弥合这一差距并使计算更靠近物联网设备。然而，雾中的资源管理以及将雾设备最佳分配给应用模块对于提高资源利用率和实现QoS至关重要。这方面的一个重大挑战是动态管理雾网络，以确定应用模块在资源上具有成本效益的放置方式。在本研究中，我们提出了智能医疗保健应用模块在雾资源上的最佳放置策略。与一些基线技术相比，该策略的目标是确保在延迟、带宽和最早完成时间方面的最佳执行。我们提出了一种受蜜蜂启发的策略，用于应用模块处理的资源分配和利用。为了对应用进行建模并衡量我们策略的有效性，基于Java的iFogSim仿真类得到了扩展，并进行了实验，实验结果令人满意。
