Jixun Gao^1,2, Bingyi Hu², Jialei Liu^3,4,*, Huaichen Wang⁵, Quanzhen Huang¹, Yuanyuan Zhao⁶

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1-16, 2023, DOI:10.32604/iasc.2023.036890

Abstract Mobile Edge Computing (MEC) is proposed to solve the needs of Internet of Things (IoT) users for high resource utilization, high reliability and low latency of service requests. However, the backup virtual machine is idle when its primary virtual machine is running normally, which will waste resources. Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization. First, these virtual machines are deployed into slots randomly, and then some tasks with cooperative relationship are offloaded to virtual machines for processing. Different deployment locations have different resource utilization and average service response time. We want to find… More >

Lenin Babu Russeliah^1,*, R. Adaline Suji², D. Bright Anand³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3925-3938, 2023, DOI:10.32604/csse.2023.034727

Abstract Cloud computing (CC) is developing as a powerful and flexible computational structure for providing ubiquitous service to users. It receives interrelated software and hardware resources in an integrated manner distinct from the classical computational environment. The variation of software and hardware resources were combined and composed as a resource pool. The software no more resided in the single hardware environment, it can be executed on the schedule of resource pools to optimize resource consumption. Optimizing energy consumption in CC environments is the question that allows utilizing several energy conservation approaches for effective resource allocation. This study introduces a Battle Royale… More >

Mohit Agarwal^1,*, Shikha Gupta²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6103-6119, 2022, DOI:10.32604/cmc.2022.030778

Abstract Task scheduling in highly elastic and dynamic processing environments such as cloud computing have become the most discussed problem among researchers. Task scheduling algorithms are responsible for the allocation of the tasks among the computing resources for their execution, and an inefficient task scheduling algorithm results in under-or over-utilization of the resources, which in turn leads to degradation of the services. Therefore, in the proposed work, load balancing is considered as an important criterion for task scheduling in a cloud computing environment as it can help in reducing the overhead in the critical decision-oriented process. In this paper, we propose… More >

M. Hema^1,*, S. Kanaga Suba Raja²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 143-156, 2023, DOI:10.32604/csse.2023.024895

Abstract In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to… 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 >

P. Anandraj^1,*, S. Ramabalan²

Computer Systems Science and Engineering, Vol.42, No.2, pp. 795-811, 2022, DOI:10.32604/csse.2022.022107

Abstract The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently. The distributed robotic control system can be used in real time for resolving various challenges such as localization, motion controlling, mapping, route planning, etc. The distributed robotic control system can manage different kinds of heterogenous devices. Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements. For instance, scheduling of resources (such as communication channel, computation unit, robot… More >

Zakir Ullah¹, Asif Umer¹, Mahdi Zaree², Jamil Ahmad¹, Faisal Alanazi^3,*, Noor Ul Amin¹, Arif Iqbal Umar¹, Ali Imran Jehangiri¹, Muhammad Adnan¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2123-2140, 2021, DOI:10.32604/cmc.2021.015445

Abstract Cloud computing is a demanding business platform for services related to the field of IT. The goal of cloud customers is to access resources at a sustainable price, while the goal of cloud suppliers is to maximize their services utilization. Previously, the customers would bid for every single resource type, which was a limitation of cloud resources allocation. To solve these issues, researchers have focused on a combinatorial auction in which the resources are offered by the providers in bundles so that the user bids for their required bundle. Still, in this allocation mechanism, some drawbacks need to be tackled,… More >

Sohan Kumar Pande¹, Sanjaya Kumar Panda², Satyabrata Das¹, Kshira Sagar Sahoo³, Ashish Kr. Luhach⁴, N. Z. Jhanjhi^5,*, Roobaea Alroobaea⁶, Sivakumar Sivanesan⁵

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2647-2663, 2021, DOI:10.32604/cmc.2021.015026

Abstract In recent years, vehicular cloud computing (VCC) has gained vast attention for providing a variety of services by creating virtual machines (VMs). These VMs use the resources that are present in modern smart vehicles. Many studies reported that some of these VMs hosted on the vehicles are overloaded, whereas others are underloaded. As a circumstance, the energy consumption of overloaded vehicles is drastically increased. On the other hand, underloaded vehicles are also drawing considerable energy in the underutilized situation. Therefore, minimizing the energy consumption of the VMs that are hosted by both overloaded and underloaded is a challenging issue in… More >

Priya Baldoss^1,2,*, Gnanasekaran Thangavel³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 253-265, 2021, DOI:10.32604/cmc.2021.013695

Abstract In the present scenario, cloud computing service provides on-request access to a collection of resources available in remote system that can be shared by numerous clients. Resources are in self-administration; consequently, clients can adjust their usage according to their requirements. Resource usage is estimated and clients can pay according to their utilization. In literature, the existing method describes the usage of various hardware assets. Quality of Service (QoS) needs to be considered for ascertaining the schedule and the access of resources. Adhering with the security arrangement, any additional code is forbidden to ensure the usage of resources complying with QoS.… More >

Sardar Khaliq uz Zaman¹, Tahir Maqsood¹, Mazhar Ali¹, Kashif Bilal¹, Sajjad A. Madani¹, Atta ur Rehman Khan^2,*

Computer Systems Science and Engineering, Vol.34, No.2, pp. 79-90, 2019, DOI:10.32604/csse.2019.34.079

Abstract Optimal task allocation in Large-Scale Computing Systems (LSCSs) that endeavors to balance the load across limited computing resources is considered an NP-hard problem. MinMin algorithm is one of the most widely used heuristic for scheduling tasks on limited computing resources. The MinMin minimizes makespan compared to other algorithms, such as Heterogeneous Earliest Finish Time (HEFT), duplication based algorithms, and clustering algorithms. However, MinMin results in unbalanced utilization of resources especially when majority of tasks have lower computational requirements. In this work we consider a computational model where each machine has certain bounded capacity to execute a predefined number of tasks… More >