Department of Communication Technology and Networks, Universiti Putra Malaysia, Serdang 43400, Malaysia.
Laboratory of Computational Science and Mathematical Physics, Institute for Mathematical Research (INSPEM), Universiti Putra Malaysia, Serdang 43400, Malaysia.
Sensors (Basel). 2021 Nov 3;21(21):7308. doi: 10.3390/s21217308.
Cloud computing is an emerging paradigm that offers flexible and seamless services for users based on their needs, including user budget savings. However, the involvement of a vast number of cloud users has made the scheduling of users' tasks (i.e., cloudlets) a challenging issue in selecting suitable data centres, servers (hosts), and virtual machines (VMs). Cloudlet scheduling is an NP-complete problem that can be solved using various meta-heuristic algorithms, which are quite popular due to their effectiveness. Massive user tasks and rapid growth in cloud resources have become increasingly complex challenges; therefore, an efficient algorithm is necessary for allocating cloudlets efficiently to attain better execution times, resource utilisation, and waiting times. This paper proposes a cloudlet scheduling, locust inspired algorithm to reduce the average makespan and waiting time and to boost VM and server utilisation. The CloudSim toolkit was used to evaluate our algorithm's efficiency, and the obtained results revealed that our algorithm outperforms other state-of-the-art nature-inspired algorithms, improving the average makespan, waiting time, and resource utilisation.
云计算是一种新兴的范例，它根据用户的需求为用户提供灵活、无缝的服务，包括用户节省预算。然而，大量的云用户的参与使得调度用户的任务（即，云）在选择合适的数据中心、服务器（主机）和虚拟机（VM）方面成为一个具有挑战性的问题。云调度是一个 NP 完全问题，可以使用各种启发式算法来解决，由于其有效性，这些算法非常受欢迎。大量的用户任务和快速增长的云资源已经成为越来越复杂的挑战；因此，需要一种有效的算法来有效地分配云，以实现更好的执行时间、资源利用率和等待时间。本文提出了一种基于蝗虫启发式的云调度算法，以减少平均完成时间和等待时间，并提高 VM 和服务器的利用率。使用 CloudSim 工具包来评估我们算法的效率，得到的结果表明，我们的算法优于其他最先进的基于自然启发的算法，提高了平均完成时间、等待时间和资源利用率。
