Abdulrahman M. Abdulghani^*

Journal on Artificial Intelligence, Vol.6, pp. 241-259, 2024, DOI:10.32604/jai.2024.056259 - 16 October 2024

Abstract Cloud computing has rapidly evolved into a critical technology, seamlessly integrating into various aspects of daily life. As user demand for cloud services continues to surge, the need for efficient virtualization and resource management becomes paramount. At the core of this efficiency lies task scheduling, a complex process that determines how tasks are allocated and executed across cloud resources. While extensive research has been conducted in the area of task scheduling, optimizing multiple objectives simultaneously remains a significant challenge due to the NP (Non-deterministic Polynomial) Complete nature of the problem. This study aims to address… More >

Nguyen Vu Anh Duy, Nguyen Le Thai, Nguyen Huu Tho^*

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 15-31, 2024, DOI:10.32604/iasc.2024.038272 - 29 March 2024

Abstract In this paper, we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail stations. In particular, the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes. A dual cycle of cranes is used to minimize the number of working cycles of cranes. The rail crane scheduling problems in this study are based on the movement of containers. We consider not only the gantry moves, but also the trolley moves as well as More >

Zhaolin Lv¹, Yuexia Zhao², Hongyue Kang^3,*, Zhenyu Gao³, Yuhang Qin⁴

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2337-2360, 2024, DOI:10.32604/cmc.2023.045826 - 27 February 2024

Abstract Flexible job shop scheduling problem (FJSP) is the core decision-making problem of intelligent manufacturing production management. The Harris hawk optimization (HHO) algorithm, as a typical metaheuristic algorithm, has been widely employed to solve scheduling problems. However, HHO suffers from premature convergence when solving NP-hard problems. Therefore, this paper proposes an improved HHO algorithm (GNHHO) to solve the FJSP. GNHHO introduces an elitism strategy, a chaotic mechanism, a nonlinear escaping energy update strategy, and a Gaussian random walk strategy to prevent premature convergence. A flexible job shop scheduling model is constructed, and the static and dynamic… More >

Sihan Wang, Xinyu Li, Qihao Liu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1871-1890, 2023, DOI:10.32604/cmes.2023.028339 - 26 June 2023

Abstract The job shop scheduling problem (JSSP) is a classical combinatorial optimization problem that exists widely in diverse scenarios of manufacturing systems. It is a well-known NP-hard problem, when the number of jobs increases, the difficulty of solving the problem exponentially increases. Therefore, a major challenge is to increase the solving efficiency of current algorithms. Modifying the neighborhood structure of the solutions can effectively improve the local search ability and efficiency. In this paper, a genetic Tabu search algorithm with neighborhood clipping (GTS_NC) is proposed for solving JSSP. A neighborhood solution clipping method is developed and… More >

Lei Yin¹, Chang Sun², Ming Gao³, Yadong Fang⁴, Ming Li¹, Fengyu Zhou^1,*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1587-1608, 2023, DOI:10.32604/iasc.2023.039380 - 21 June 2023

Abstract The solution strategy of the heuristic algorithm is pre-set and has good performance in the conventional cloud resource scheduling process. However, for complex and dynamic cloud service scheduling tasks, due to the difference in service attributes, the solution efficiency of a single strategy is low for such problems. In this paper, we presents a hyper-heuristic algorithm based on reinforcement learning (HHRL) to optimize the completion time of the task sequence. Firstly, In the reward table setting stage of HHRL, we introduce population diversity and integrate maximum time to comprehensively determine the task scheduling and the 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 - 03 April 2023

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… More >

Poonam^*, Suman Sangwan

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1783-1799, 2023, DOI:10.32604/cmc.2023.031729 - 22 September 2022

Abstract This paper presents a novel fuzzy firefly-based intelligent algorithm for load balancing in mobile cloud computing while reducing makespan. The proposed technique implicitly acts intelligently by using inherent traits of fuzzy and firefly. It automatically adjusts its behavior or converges depending on the information gathered during the search process and objective function. It works for 3-tier architecture, including cloudlet and public cloud. As cloudlets have limited resources, fuzzy logic is used for cloudlet selection using capacity and waiting time as input. Fuzzy provides human-like decisions without using any mathematical model. Firefly is a powerful meta-heuristic… More >

B. Chellapraba^1,*, D. Manohari², K. Periyakaruppan³, M. S. Kavitha⁴

Computer Systems Science and Engineering, Vol.45, No.1, pp. 483-495, 2023, DOI:10.32604/csse.2023.029854 - 16 August 2022

Abstract Owing to massive technological developments in Internet of Things (IoT) and cloud environment, cloud computing (CC) offers a highly flexible heterogeneous resource pool over the network, and clients could exploit various resources on demand. Since IoT-enabled models are restricted to resources and require crisp response, minimum latency, and maximum bandwidth, which are outside the capabilities. CC was handled as a resource-rich solution to aforementioned challenge. As high delay reduces the performance of the IoT enabled cloud platform, efficient utilization of task scheduling (TS) reduces the energy usage of the cloud infrastructure and increases the income… More >

J. Jean Justus¹, U. Sakthi², K. Priyadarshini³, B. Thiyaneswaran⁴, Masoud Alajmi⁵, Marwa Obayya⁶, Manar Ahmed Hamza^7,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 205-219, 2023, DOI:10.32604/csse.2023.025256 - 01 June 2022

Abstract The developments of multi-core systems (MCS) have considerably improved the existing technologies in the field of computer architecture. The MCS comprises several processors that are heterogeneous for resource capacities, working environments, topologies, and so on. The existing multi-core technology unlocks additional research opportunities for energy minimization by the use of effective task scheduling. At the same time, the task scheduling process is yet to be explored in the multi-core systems. This paper presents a new hybrid genetic algorithm (GA) with a krill herd (KH) based energy-efficient scheduling technique for multi-core systems (GAKH-SMCS). The goal of… More >

Mohit Agarwal^1,*, Shikha Gupta²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6103-6119, 2022, DOI:10.32604/cmc.2022.030778 - 28 July 2022

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.… More >