Abdulelah Alwabel^1,*, Chinmaya Kumar Swain²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4127-4148, 2024, DOI:10.32604/cmc.2024.048833 - 20 June 2024

Abstract Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources. However, the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes, thus making the application placement problem more complex than that in cloud computing. An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the… More >

Nidhika Chauhan¹, Navneet Kaur², Kamaljit Singh Saini³, Sahil Verma³, Kavita³, Ruba Abu Khurma^4,5, Pedro A. Castillo^6,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3757-3782, 2024, DOI:10.32604/cmc.2024.046516 - 20 June 2024

Abstract Cloud computing is a dynamic and rapidly evolving field, where the demand for resources fluctuates continuously. This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments. The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently. By adhering to the proposed resource allocation method, we aim to achieve a substantial reduction in energy consumption. This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most, aligning with the broader goal of… More >

Nidhika Chauhan¹, Navneet Kaur², Kamaljit Singh Saini², Sahil Verma³, Abdulatif Alabdulatif⁴, Ruba Abu Khurma^5,7, Maribel Garcia-Arenas⁶, Pedro A. Castillo^6,*

Computer Systems Science and Engineering, Vol.48, No.3, pp. 571-608, 2024, DOI:10.32604/csse.2024.042690 - 20 May 2024

Abstract As cloud computing usage grows, cloud data centers play an increasingly important role. To maximize resource utilization, ensure service quality, and enhance system performance, it is crucial to allocate tasks and manage performance effectively. The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers. The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies, categories, and gaps. A literature review was conducted, which included the analysis of 463 task allocations and 480 performance management papers. The… More >

Muchang Rao, Hang Qin^*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2647-2672, 2024, DOI:10.32604/cmc.2024.050380 - 15 May 2024

Abstract More devices in the Intelligent Internet of Things (AIoT) result in an increased number of tasks that require low latency and real-time responsiveness, leading to an increased demand for computational resources. Cloud computing’s low-latency performance issues in AIoT scenarios have led researchers to explore fog computing as a complementary extension. However, the effective allocation of resources for task execution within fog environments, characterized by limitations and heterogeneity in computational resources, remains a formidable challenge. To tackle this challenge, in this study, we integrate fog computing and cloud computing. We begin by establishing a fog-cloud environment… More >

Umi Salma Basha¹, Shashi Kant Gupta², Wedad Alawad³, SeongKi Kim^4,*, Salil Bharany^5,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3397-3416, 2024, DOI:10.32604/cmc.2024.046265 - 15 May 2024

Abstract A new era of data access and management has begun with the use of cloud computing in the healthcare industry. Despite the efficiency and scalability that the cloud provides, the security of private patient data is still a major concern. Encryption, network security, and adherence to data protection laws are key to ensuring the confidentiality and integrity of healthcare data in the cloud. The computational overhead of encryption technologies could lead to delays in data access and processing rates. To address these challenges, we introduced the Enhanced Parallel Multi-Key Encryption Algorithm (EPM-KEA), aiming to bolster… More >

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 - 27 February 2024

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… 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 - 27 February 2024

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… 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 - 30 January 2024

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,… 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 - 30 January 2024

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.… 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 - 30 December 2023

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.… More >