سامانه پشتیبانی خدمات اطلاعات

  اخبار و اعلانات

 آمار

تعداد نشریات158
تعداد شماره‌ها6,232
تعداد مقالات67,799
تعداد مشاهده مقاله115,275,360
تعداد دریافت فایل اصل مقاله90,020,565
. (1400). Priority-Oriented Task Scheduling based on Harris Hawks Optimizer for Cloud Computing. , (), 1-40. doi: 10.22059/jac.2022.85501
. "Priority-Oriented Task Scheduling based on Harris Hawks Optimizer for Cloud Computing". , , , 1400, 1-40. doi: 10.22059/jac.2022.85501
. (1400). 'Priority-Oriented Task Scheduling based on Harris Hawks Optimizer for Cloud Computing', , (), pp. 1-40. doi: 10.22059/jac.2022.85501
. Priority-Oriented Task Scheduling based on Harris Hawks Optimizer for Cloud Computing. , 1400; (): 1-40. doi: 10.22059/jac.2022.85501

Priority-Oriented Task Scheduling based on Harris Hawks Optimizer for Cloud Computing

Journal of Algorithms and Computation
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 25 دی 1400    اصل مقاله (1.46 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jac.2022.85501
چکیده
 Cloud computing is a high-performance computing environment that can remotely provide services to customers using a pay-per-use model. The principal challenge in cloud computing is task scheduling, in which tasks must be effectively allocated to resources. The mapping of cloud resources to customer requests (tasks) is a popular Nondeterministic Polynomial-time (NP)-Complete problem. Although the task scheduling problem is a multi-objective optimization problem, most task scheduling algorithms cannot provide an effective trade-off between makespan, resource utilization, and energy consumption. Therefore, this study introduces a Priority-based task scheduling algorithm using Harris Hawks Optimizer (HHO) which is entitled as PHHO. The proposed algorithm first prioritizes tasks using a hierarchical process based on length and memory. Then, the HHO algorithm is used for optimally assigning tasks to resources. The PHHO algorithm aims to decrease makespan and energy consumption while increasing resource utilization and throughput. To evaluate the effectiveness of the PHHO algorithm, it is compared with other well-known meta-heuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA), and Moth-Flame Optimization (MFO). The experimental results show the effectiveness of the PHHO algorithm compared to other algorithms in terms of makespan, resource utilization, throughput, and energy consumption.
کلیدواژه‌ها
Cloud؛ Task scheduling؛ Meta-heuristic؛ Task priority
آمار
تعداد مشاهده مقاله: 142
تعداد دریافت فایل اصل مقاله: 107


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب