A Discrete Prey-Predator Algorithm for Cloud Task Scheduling

Cloud computing is considered a key Internet technology. Cloud providers offer services through the Internet, such as infrastructure, platforms, and software. The scheduling process of cloud providers' tasks concerns allocating clients' tasks to providers' resources. Several mechanisms have been developed for task scheduling in cloud computing. Still, these mechanisms need to be optimized for execution time and makespan. This paper presents a new task-scheduling mechanism based on Discrete Prey-Predator to optimize the task-scheduling process in the cloud environment. The proposed Discrete Prey-Predator mechanism assigns each scheduling solution survival values. The proposed mechanism denotes the prey's maximum surviving value and the predator's minimum surviving value. The proposed Discrete Prey-Predator mechanism aims to minimize the execution time of tasks in cloud computing. This paper makes a significant contribution to the field of cloud task scheduling by introducing a new mechanism based on the Discrete Prey-Predator algorithm. The Discrete Prey-Predator mechanism presents distinct advantages, including optimized task execution, as the mechanism is purpose-built to optimize task execution times in cloud computing, improving overall system efficiency and resource utilization. Moreover, the proposed mechanism introduces a survival-value-based approach, as the mechanism introduces a unique approach for assigning survival values to scheduling solutions, differentiating between the prey's maximum surviving value and the predator's minimum surviving value. This improvement enhances decision-making precision in task allocation. To evaluate the proposed mechanism, simulations using the CloudSim simulator were conducted. The experiment phase considered different scenarios for testing the proposed mechanism in different states. The simulation results revealed that the proposed Discrete Prey-Predator mechanism has shorter execution times than the firefly algorithm. The average of the five execution times of the Discrete Prey-Predator mechanism was 270.97 s, while the average of the five execution times of the firefly algorithm was 315.10 s.

Automated summary

This paper presents a new task-scheduling mechanism based on the Discrete Prey-Predator algorithm to optimize the task-scheduling process in cloud computing. The mechanism assigns survival values to scheduling solutions, aiming to minimize task execution time and improve overall system efficiency and resource utilization. Simulation results show that the proposed mechanism has shorter execution times compared to the firefly algorithm.