Load balancing is a challenge in the cloud network for proper resource utilization and improvement of makespan. To overcome the problem of load balancing various static and dynamic scheduling methods come into existence. In this paper, we have proposed two multi-datacenter two-phase load adjustment techniques for load balancing and apposite task scheduling. Our proposed methods allocate user jobs to different virtual machines present in different datacenters based on better makespan. Here we have considered communication delay and bandwidth requirement for inter-datacenter task migration. The simulation result specifies that proposed techniques give a significant improvement in makespan and resource utilization when compared with existing algorithms.

负载平衡是云网络中如何正确利用资源和改善生产期的挑战。为了克服负载平衡的问题，存在各种静态和动态调度方法。在本文中，我们提出了两种多数据中心两阶段负载调整技术，用于负载均衡和适当的任务调度。我们提出的方法会根据更好的有效期将用户作业分配给位于不同数据中心的不同虚拟机。在这里，我们考虑了数据中心间任务迁移的通信延迟和带宽要求。仿真结果表明，与现有算法相比，所提出的技术在制造时间和资源利用率方面有显着提高。