Energy Efficient Placement of Workloads in Composable Data Center Networks
Energy Efficient Placement of Workloads in Composable Data Center Networks
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DOI：
10.1109/jlt.2021.3063325
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发表时间：
2021-01
影响因子：
4.7
通讯作者：
O. Ajibola;T. El-Gorashi;J. Elmirghani
中科院分区：
文献类型：
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作者：
O. Ajibola;T. El-Gorashi;J. Elmirghani
本文研究网络拓扑上可组合数据中心（DC）基础设施的能源效率。使用一个混合整数线性规划（MILP）模型，我们比较了在机架规模和豆荚规模在选定的电气，光学和混合网络拓扑结构相对于传统的DC解聚的性能。相对于一个豆荚规模的DC，结果表明，在机架规模的物理解聚是足够的光网络拓扑结构时，采用最佳的效率，并以适当的方式分配资源组件。光网络拓扑还实现了可组合DC中的最佳能量效率。本文还研究了传统的DC服务器在光网络拓扑结构的逻辑分解。相对于机架规模的物理分解，每个机架内的服务器资源的逻辑分解由于改进的资源需求放置而使得总DC功耗（TDPC）的边际下降。因此，能够实现能够支持存储器（访问）延迟敏感和不敏感工作负载两者的可适应的可组合基础设施。我们还进行了研究，采用微服务架构在传统的和可组合的DC。我们的研究结果表明，增加工作负载的模块化提高了传统DC的能源效率，但DC资源的不成比例的利用仍然存在。分解和微服务的组合通过实现最佳的资源利用和能源效率，使传统DC的TDPC减少了23%。最后，我们提出了一个启发式的能源效率的工作负载在可组合DC复制的趋势，在本文中制定的MILP模型放置。
This paper studies the energy efficiency of composable data center (DC) infrastructures over network topologies. Using a mixed integer linear programming (MILP) model, we compare the performance of disaggregation at rack-scale and pod-scale over selected electrical, optical and hybrid network topologies relative to a traditional DC. Relative to a pod-scale DC, the results show that physical disaggregation at rack-scale is sufficient for optimal efficiency when the optical network topology is adopted, and resource components are allocated in a suitable manner. The optical network topology also enables optimal energy efficiency in composable DCs. The paper also studies logical disaggregation of traditional DC servers over an optical network topology. Relative to physical disaggregation at rack-scale, logical disaggregation of server resources within each rack enables marginal fall in the total DC power consumption (TDPC) due to improved resource demands placement. Hence, an adaptable composable infrastructure that can support both in memory (access) latency sensitive and insensitive workloads is enabled. We also conduct a study of the adoption of micro-service architecture in both traditional and composable DCs. Our results show that increasing the modularity of workloads improves the energy efficiency in traditional DCs, but disproportionate utilization of DC resources persists. A combination of disaggregation and micro-services achieved up to 23% reduction in the TDPC of the traditional DC by enabling optimal resources utilization and energy efficiencies. Finally, we propose a heuristic for energy efficient placement of workloads in composable DCs which replicates the trends produced by the MILP model formulated in this paper.