Chirag Chandrashekar¹, Pradeep Krishnadoss^1,*, Vijayakumar Kedalu Poornachary¹, Balasundaram Ananthakrishnan^1,2

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2593-2616, 2024, DOI:10.32604/cmc.2024.046304

Abstract Cloud computing provides a diverse and adaptable resource pool over the internet, allowing users to tap into various resources as needed. It has been seen as a robust solution to relevant challenges. A significant delay can hamper the performance of IoT-enabled cloud platforms. However, efficient task scheduling can lower the cloud infrastructure’s energy consumption, thus maximizing the service provider’s revenue by decreasing user job processing times. The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm (MCWOA), combines elements of the Chimp Optimization Algorithm (COA) and the Whale Optimization Algorithm (WOA). To enhance MCWOA’s identification precision, the Sobol sequence… More >

Nader Abdel Karim^1,*, Osama A. Khashan^2,*, Waleed K. Abdulraheem³, Moutaz Alazab¹, Hasan Kanaker⁴, Mahmoud E. Farfoura⁵, Mohammad Alshinwan^5,6

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2023-2045, 2024, DOI:10.32604/cmc.2023.044304

Abstract As the extensive use of cloud computing raises questions about the security of any personal data stored there, cryptography is being used more frequently as a security tool to protect data confidentiality and privacy in the cloud environment. A hypervisor is a virtualization software used in cloud hosting to divide and allocate resources on various pieces of hardware. The choice of hypervisor can significantly impact the performance of cryptographic operations in the cloud environment. An important issue that must be carefully examined is that no hypervisor is completely superior in terms of performance; Each hypervisor should be examined to meet… More >

Shasha Zhao^1,2,3,*, Huanwen Yan^1,2, Qifeng Lin^1,2, Xiangnan Feng^1,2, He Chen^1,2, Dengyin Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1135-1156, 2024, DOI:10.32604/cmc.2024.045660

Abstract Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment. Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios. In this work, the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm (HPSO-EABC) has been proposed, which hybrids our presented Evolutionary Artificial Bee Colony (EABC), and Hierarchical Particle Swarm Optimization (HPSO) algorithm. The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm. Comprehensive testing including evaluations of algorithm convergence speed, resource execution time, load balancing,… More >

Sarah Mustafa Eljack^1,*, Mahdi Jemmali^2,3,4, Mohsen Denden^6,7, Mutasim Al Sadig¹, Abdullah M. Algashami¹, Sadok Turki⁵

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1461-1479, 2024, DOI:10.32604/cmc.2023.040919

Abstract In the cloud environment, ensuring a high level of data security is in high demand. Data planning storage optimization is part of the whole security process in the cloud environment. It enables data security by avoiding the risk of data loss and data overlapping. The development of data flow scheduling approaches in the cloud environment taking security parameters into account is insufficient. In our work, we propose a data scheduling model for the cloud environment. The model is made up of three parts that together help dispatch user data flow to the appropriate cloud VMs. The first component is the… More >

Salam Al-E’mari¹, Yousef Sanjalawe^2,*, Ahmad Al-Daraiseh³, Mohammad Bany Taha⁴, Mohammad Aladaileh²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 1-41, 2024, DOI:10.32604/cmes.2023.043627

Abstract Amid the landscape of Cloud Computing (CC), the Cloud Datacenter (DC) stands as a conglomerate of physical servers, whose performance can be hindered by bottlenecks within the realm of proliferating CC services. A linchpin in CC’s performance, the Cloud Service Broker (CSB), orchestrates DC selection. Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck, endangering service quality. To tackle this, deploying an efficient CSB policy becomes imperative, optimizing DC selection to meet stringent Quality-of-Service (QoS) demands. Amidst numerous CSB policies, their implementation grapples with challenges like costs and availability. This article undertakes a holistic… More >

Riza Altunay^1,2,*, Omer Faruk Bay³

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2881-2897, 2023, DOI:10.32604/cmc.2023.042340

Abstract The use of fog computing in the Internet of Things (IoT) has emerged as a crucial solution, bringing cloud services closer to end users to process large amounts of data generated within the system. Despite its advantages, the increasing task demands from IoT objects often overload fog devices with limited resources, resulting in system delays, high network usage, and increased energy consumption. One of the major challenges in fog computing for IoT applications is the efficient deployment of services between fog clouds. To address this challenge, we propose a novel Optimal Foraging Algorithm (OFA) for task placement on appropriate fog… More >

Laila Almutairi¹, Shabnam Mohamed Aslam^2,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2791-2811, 2023, DOI:10.32604/cmc.2023.040268

Abstract The rapid growth of service-oriented and cloud computing has created large-scale data centres worldwide. Modern data centres’ operating costs mostly come from back-end cloud infrastructure and energy consumption. In cloud computing, extensive communication resources are required. Moreover, cloud applications require more bandwidth to transfer large amounts of data to satisfy end-user requirements. It is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching buffers. This paper proposes a novel Energy and Communication (EC) aware scheduling (EC-scheduler) algorithm for green cloud computing, which optimizes data centre energy consumption and traffic load. The primary goal… More >

Rayan A. Alsemmeari^1,*, Mohamed Yehia Dahab², Badraddin Alturki¹, Abdulaziz A. Alsulami³

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1853-1870, 2023, DOI:10.32604/cmc.2023.038589

Abstract Emerging telemedicine trends, such as the Internet of Medical Things (IoMT), facilitate regular and efficient interactions between medical devices and computing devices. The importance of IoMT comes from the need to continuously monitor patients’ health conditions in real-time during normal daily activities, which is realized with the help of various wearable devices and sensors. One major health problem is workplace stress, which can lead to cardiovascular disease or psychiatric disorders. Therefore, real-time monitoring of employees’ stress in the workplace is essential. Stress levels and the source of stress could be detected early in the fog layer so that the negative… More >

Jiahao Zhang, Honglin Wang^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2427-2441, 2023, DOI:10.32604/cmc.2023.038462

Abstract With the rapid development of technology, processing the explosive growth of meteorological data on traditional standalone computing has become increasingly time-consuming, which cannot meet the demands of scientific research and business. Therefore, this paper proposes the implementation of the parallel Clustering Large Application based upon RANdomized Search (CLARANS) clustering algorithm on the Spark cloud computing platform to cluster China’s climate regions using meteorological data from 1988 to 2018. The aim is to address the challenge of applying clustering algorithms to large datasets. In this paper, the morphological similarity distance is adopted as the similarity measurement standard instead of Euclidean distance,… More >

Kaili Shao¹, Hui Fu¹, Ying Song², Bo Wang^3,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2259-2274, 2023, DOI:10.32604/csse.2023.041454

Abstract To serve various tasks requested by various end devices with different requirements, end-edge-cloud (E2C) has attracted more and more attention from specialists in both academia and industry, by combining both benefits of edge and cloud computing. But nowadays, E2C still suffers from low service quality and resource efficiency, due to the geographical distribution of edge resources and the high dynamic of network topology and user mobility. To address these issues, this paper focuses on task offloading, which makes decisions that which resources are allocated to tasks for their processing. This paper first formulates the problem into binary non-linear programming and… More >