P. Ramadevi^1,*, T. Jayasankar¹, V. Dinesh², M. Dhamodaran³

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1373-1385, 2023, DOI:10.32604/csse.2023.026603

Abstract Recently, with the growth of cyber physical systems (CPS), several applications have begun to deploy in the CPS for connecting the cyber space with the physical scale effectively. Besides, the cloud computing (CC) enabled CPS offers huge processing and storage resources for CPS that finds helpful for a range of application areas. At the same time, with the massive development of applications that exist in the CPS environment, the energy utilization of the cloud enabled CPS has gained significant interest. For improving the energy effectiveness of the CC platform, virtualization technologies have been employed for resource management and the applications… More >

N. Jagadeeswari^1,*, V. Mohan Raj²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 929-943, 2023, DOI:10.32604/csse.2023.024945

Abstract Virtualization is the backbone of cloud computing, which is a developing and widely used paradigm. By finding and merging identical memory pages, memory deduplication improves memory efficiency in virtualized systems. Kernel Same Page Merging (KSM) is a Linux service for memory pages sharing in virtualized environments. Memory deduplication is vulnerable to a memory disclosure attack, which uses covert channel establishment to reveal the contents of other colocated virtual machines. To avoid a memory disclosure attack, sharing of identical pages within a single user’s virtual machine is permitted, but sharing of contents between different users is forbidden. In our proposed approach,… More >

J. Noorul Ameen^1,*, S. Jabeen Begum²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1281-1294, 2022, DOI:10.32604/iasc.2022.025137

Abstract In the present decade, the development of cloud computing framework is witnessed for providing computational resources by dynamic service providing methods. There are many problems in load balancing in cloud, when there is a huge demand for resources. The objective of load balancing is to equilibrate the cloud server computations for avoiding overloading problems. On addressing the issue, this paper develops a new model called Evolutionary Algorithm based Adaptive Load Balancing (EA-ALB) for enhancing the efficacy and user satisfaction of cloud services. Efficient Scheduling Scheme for the virtual machines using machine learning algorithm is proposed in this work. Initially, process… More >

Nawaf Alhebaishi¹, Abdulrhman M. Alshareef¹, Tawfiq Hasanin¹, Raed Alsini¹, Gyanendra Prasad Joshi², Seongsoo Cho³, Doo Ill Chul^4,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5233-5250, 2022, DOI:10.32604/cmc.2022.025596

Abstract In recent times, internet of things (IoT) applications on the cloud might not be the effective solution for every IoT scenario, particularly for time sensitive applications. A significant alternative to use is edge computing that resolves the problem of requiring high bandwidth by end devices. Edge computing is considered a method of forwarding the processing and communication resources in the cloud towards the edge. One of the considerations of the edge computing environment is resource management that involves resource scheduling, load balancing, task scheduling, and quality of service (QoS) to accomplish improved performance. With this motivation, this paper presents new… More >

B. Gomathi¹, B. Saravana Balaji², V. Krishna Kumar³, Mohamed Abouhawwash^4,5,*, Sultan Aljahdali⁶, Mehedi Masud⁶, Nina Kuchuk⁷

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1771-1785, 2022, DOI:10.32604/iasc.2022.024052

Abstract Cloud computing enables cloud providers to outsource their Information Technology (IT) services from data centers in a pay-as-you-go model. However, Cloud infrastructure comprises virtualized physical resources that consume huge amount of energy and emits carbon footprints to environment. Hence, there should be focus on optimal assignment of Virtual Machines (VM) to Physical Machines (PM) to ensure the energy efficiency and service level performance. In this paper, The Pareto based Multi-Objective Particle Swarm Optimization with Composite Mutation (PSOCM) technique has been proposed to improve the energy efficiency and minimize the Service Level Agreement (SLA) violation in Cloud Environment. In this paper,… More >

R. Swathy^*, B. Vinayagasundaram

Computer Systems Science and Engineering, Vol.43, No.1, pp. 159-174, 2022, DOI:10.32604/csse.2022.023706

Abstract This paper proposes an algorithm for scheduling Virtual Machines (VM) with energy saving strategies in the physical servers of cloud data centers. Energy saving strategy along with a solution for productive resource utilization for VM deployment in cloud data centers is modeled by a combination of “Virtual Machine Scheduling using Bayes Theorem” algorithm (VMSBT) and Virtual Machine Migration (VMMIG) algorithm. It is shown that the overall data center’s consumption of energy is minimized with a combination of VMSBT algorithm and Virtual Machine Migration (VMMIG) algorithm. Virtual machine migration between the active physical servers in the data center is carried out… More >

M. Manikandan^1,*, R. Subramanian², M. S. Kavitha³, S. Karthik³

Computer Systems Science and Engineering, Vol.42, No.3, pp. 935-948, 2022, DOI:10.32604/csse.2022.021816

Abstract In today’s world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale consumer applications in a pay-by-use… More >

Denghui Zhang^1,*, Guocai Yin²

Journal on Internet of Things, Vol.3, No.4, pp. 149-157, 2021, DOI:10.32604/jiot.2021.016936

Abstract Cloud data centers face the largest energy consumption. In order to save energy consumption in cloud data centers, cloud service providers adopt a virtual machine migration strategy. In this paper, we propose an efficient virtual machine placement strategy (VMP-SI) based on virtual machine selection and integration. Our proposed VMP-SI strategy divides the migration process into three phases: physical host state detection, virtual machine selection and virtual machine placement. The local regression robust (LRR) algorithm and minimum migration time (MMT) policy are individual used in the first and section phase, respectively. Then we design a virtual machine migration strategy that integrates… More >

S. Manikandan^1,*, M. Chinnadurai²

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1459-1466, 2022, DOI:10.32604/iasc.2022.022527

Abstract Load Balancing is an important factor handling resource during running and execution time in real time applications. Virtual machines are used for dynamically access and share the resources. As per current scenario cloud computing is played major for storage, resource accessing, resource pooling and internet based service offering. Usage of cloud computing services is dynamically increased such as online shopping, education, ticketing, etc. Many users can use the cloud resources and load balancing is used for adjusting the virtual machine and balance the node. Our proposed virtualized genetic algorithms are to provide balanced virtual machine services in Hybrid cloud. The… More >

Liang Dai¹, AoSong He¹, Guang Sun^1,3, Yuxing Pan^2,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1831-1842, 2022, DOI:10.32604/iasc.2022.022438

Abstract In order to unify the management and scheduling of cloud resources, cloud platforms use virtualization technology to re-integrate multiple computing resources in the cloud and build virtual units on physical machines to achieve dynamic provisioning of resources by configuring virtual units of various sizes. Therefore, how to reasonably determine the mapping relationship between virtual units and physical machines is an important research topic for cloud resource scheduling. In this paper, we propose a fair cloud virtual machine resource allocation method of using the stable matching theory. Our allocation method considers the allocation of resources from both user’s demand and cloud… More >