A Sustainable IoT Infrastructure Based Design of Green Cloud Computing: A Comprehensive Survey
Abdul Rauf, Sarhad University of Science and Information Technology, Peshawar Pakistan.
Fasee Ullah, Sarhad University of Science and Information Technology, Peshawar Pakistan.
Shahid Latif, Sarhad University of Science and Information Technology, Peshawar Pakistan.
Arshad Khan, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Farman Hassan, Department of Computer Science, University of Bologna, Italy.
Arif Khursheed, Sarhad University of Science and Information Technology, Peshawar Pakistan.
Corresponding Author:
Fasee Ullah (fasee.csit@suit.edu.pk)
Abstract:
Cloud simulators are tools that allow the research community, cloud service providers, and developers to test and evaluate cloud computing systems in a simulated environment. Cloud simulators are used for modelling and the simulation of computational energy resources. Additionally, cloud simulators can simulate network topologies and message-passing applications. Cloud computing has become a prevalent technology due to virtualization and cost-efficient pricing. Evaluating the efficiency of cloud resource allocation and ensuring that cloud systems meet QoS standards presents a significant challenge. However, many challenges exist realism, resource requirements, complexity, flexibility, and scalability. Real-world experimentation is costly and challenging, which leads to a focus on developing cloud simulation frameworks that cover limited aspects of the system components. The above challenges are categorized based on the impact on the cloud simulation and their nature. Our work differs from the existing work, and we focused on two aspects: the challenges of existing work and the future challenges and how the challenges can be addressed. Therefore, selecting the appropriate tool requires thoroughly comparing available simulators based on their various features. This study presents a comparison of 33 tools for cloud computing. This analysis allows readers to evaluate the leading simulators in terms of their supported models, architectural design, and essential features. Moreover, this study provides a better solution for the existing challenges to using distributed simulation approaches, parallel processing, and simulation services based on the cloud to enhance the scalability and utilization of machine learning approaches to improve realism further. It also offers guidance on selecting the most appropriate tool for researchers, providers, and cloud managers. It concludes by identifying open questions and outlining future research opportunities.
Keywords:
Cloud Computing; Simulators; Public Cloud; Private Cloud; Resources Management