Cloud computing has evolved as a new paradigm in Internet computing, offering services to the end-users and large-organizations, on-demand and pay-per-the-usage basis with high availability, elasticity, scalability and resiliency. In order to improve the performance of the Cloud system, handling multiple heterogeneous tasks concurrently, an appropriate task scheduler is required. To meet the user’s requirements in terms of Quality of Service (QoS) parameters, the task scheduling algorithm should identify the order in which tasks should be executed. Energy efficiency is the significant challenge in today’s task scheduling to meet the prerequisite for green computing. By increasing resource utilization at the data centers, virtual machine (VM) Consolidation is also recognized as the most widely used and promising approach in terms of energy consumption and system performance. However, excessive VM Consolidation could constitute a violation of the Service Level Agreement (SLA). The paper makes a contribution by outlining the numerous approaches that researchers have used thus far to achieve the goals of scheduling and VM Consolidation, assuring energy efficiency, and maintaining system performance. This would give readers a better understanding of the problems and the potential for improvement while assisting them in selecting the ideal scheduling algorithm with Consolidation technique. Additionally, the techniques are divided into three categories: those that primarily focus on task scheduling; those that target Consolidation; and complete computation, integrating task scheduling with VM Consolidation. Further classification for the scheduling algorithms include heuristic, meta-heuristic, greedy, and hybrid task scheduling algorithms. In addition to a summary of the benefits and drawbacks of the suggested algorithms, prospective research directions and recent developments in this area is also covered in this paper.

云计算已发展成为互联网计算的新范式，为最终用户和大型组织提供按需和按使用付费的服务，具有高可用性、弹性、可扩展性和弹性。为了提高云系统的性能，同时处理多个异构任务，需要合适的任务调度器。为了满足用户对服务质量（QoS）参数的要求，任务调度算法应该确定任务的执行顺序。能源效率是当今任务调度中满足绿色计算先决条件的重大挑战。通过提高数据中心的资源利用率，虚拟机 (VM) 整合也被认为是在能耗和系统性能方面使用最广泛、最有前景的方法。但是，过度的虚拟机整合可能会违反服务级别协议 (SLA)。该论文概述了研究人员迄今为止为实现调度和虚拟机整合、确保能源效率和维持系统性能等目标而使用的多种方法，从而做出了贡献。这将使读者更好地理解问题和改进的潜力，同时帮助他们使用合并技术选择理想的调度算法。此外，这些技术分为三类：主要关注任务调度的技术；那些以整合为目标的；并完成计算，将任务调度与 VM Consolidation 集成。调度算法的进一步分类包括启发式、元启发式、贪婪和混合任务调度算法。除了总结建议算法的优点和缺点之外，本文还介绍了该领域的前瞻性研究方向和最新进展。