Energy efficiency is a contemporary and challenging issue in geographically distributed data centers. These data centers consume significantly high energy and cast a negative impact on the energy resources and environment. To minimize the energy cost and the environmental impacts, Internet service providers use different approaches such as geographical load balancing (GLB). GLB refers to the placement of data centers in diverse geolocations to exploit variations in electricity prices with the objective to minimize the total energy cost. GLB helps to minimize the overall energy cost, achieve quality of service, and maximize resource utilization in geo‐distributed data centers by employing optimal workload distribution and resource utilization in the real time. In this paper, we summarize various optimization‐based workload distribution strategies and optimization techniques proposed in recent research works based on commonly used optimization factors such as workload type, load balancer, availability of renewable energy, energy storage, and data center server specification in geographically distributed data centers. The survey presents a systemized and a novel taxonomy of workload distribution in data centers. Moreover, we also debate various challenges and open research issues along with their possible solutions.

中文翻译：

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地理分布的数据中心中基于优化的工作负载分布：一项调查

在地理分布的数据中心中，能源效率是一个当代且具有挑战性的问题。这些数据中心消耗大量能源，并对能源和环境产生负面影响。为了最大程度地降低能源成本和环境影响，Internet服务提供商使用了不同的方法，例如地理负载平衡（G L B）。GLB是指将数据中心放置在不同的地理位置，以利用电价的变化，目的是最大程度地降低总能源成本。GLB通过实时采用最佳工作负载分配和资源利用率，有助于最大程度地降低总体能源成本，提高服务质量并最大限度地提高地理分布数据中心的资源利用率。在本文中，我们基于工作负载类型，负载平衡器，可再生能源的可用性，能源存储和地理区域内的数据中心服务器规范等常用的优化因素，总结了近期研究工作中提出的各种基于优化的工作负载分配策略和优化技术。分布式数据中心。该调查提出了数据中心工作量分配的系统化和新颖分类法。