虚拟化云环境下云资源供应链管理的多层体系结构:一种基于蚁群优化和生成树的云资源供应链管理新技术

Pub Date : 2021-07-01 DOI:10.4018/ijisscm.2021070101
Muhammad Aliyu, M. Murali, A. Y. Gital, S. Boukari, Rumana Kabir, M. Musa, F. Zambuk, Joshua Caleb Shawulu, I. Umar
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引用次数: 1

摘要

随着云资源需求的增长,作为云计算核心功能的供应链管理面临严峻挑战。许多研究人员已经提出了相当多的技术来应对这样的挑战。因此,许多拟议的战略仍在考虑和修改中,以增强其潜力。针对这一挑战,提出了一种结合多种算法特点的动态优化方案。该混合方案结合了蚁群优化(ACO)的元启发式群体机制和确定性生成树(SPT)算法,获得了更快的收敛链,保证了以最小的时间和成本利用资源。与SPT、轮询(RR)和抢占式公平调度算法(PFSA)相比,在cloudsim模拟器中进行的大量实验提供了最小化完工时间和吞吐量的有效结果,因为它显着提高了性能。
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A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Virtualized Cloud Environment: A Novel SCM Technique for Cloud Resources Using Ant Colony Optimization and Spanning Tree
As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.
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