On Energy Efficiency of Networks for Composable Datacentre Infrastructures

This paper evaluates the optimal scale of datacentre (DC) resource disaggregation for composable DC infrastructures and investigates the impact of present day silicon photonics technologies on the energy efficiency of different composable DC infrastructures. We formulated a mixed integer linear programming (MILP) model to this end. Our results show that present day silicon photonics technologies enable better network energy efficiency for rack-scale composable DCs compared to pod-scale composable DCs despite reported similarities in CPU and memory resource power consumption

A Network Topology for Composable Infrastructures

This paper proposes a passive optical backplane as a new network topology for composable computing infrastructures. The topology provides a high capacity, low-latency and flexible fabric that interconnects disaggregated resource components. The network topology is dedicated to inter-resource communication between composed logical hosts to ensure effective performance. We formulated a mixed integer linear programming (MILP) model that dynamically creates logical networks to support intra logical host communication over the physical network topology. The MILP performs energy efficient logical network instantiation given each application's resource demand. The topology can achieve 1 Tbps capacity per resource node given appropriate wavelength transmission data rate and the right number of wavelengths per node

An Adaptable Optimal Network Topology Model for Efficient Data Centre Design in Storage Area Networks

In this research, we look at how different network topologies affect the energy consumption of modular data centre (DC) setups. We use a combined-input directed approach to assess the benefits of rack-scale and pod-scale fragmentation across a variety of electrical, optoelectronic, and composite network architectures in comparison to a conventional DC. When the optical transport architecture is implemented and the appropriate resource components are distributed, the findings reveal fragmentation at the layer level is adequate, even compared to a pod-scale DC. Composable DCs can operate at peak efficiency because of the optical network topology. Logical separation of conventional DC servers across an optical network architecture is also investigated in this article. When compared to physical decentralisation at the rack size, logical decomposition of data centers inside each rack offers a small decrease in the overall DC energy usage thanks to better resource needs allocation. This allows for a flexible, composable architecture that can accommodate performance based in-memory applications. Moreover, we look at the state of fundamentalmodel and its use in both static and dynamic data centres. According to our findings, typical DCs become more energy efficient when workload modularity increases, although excessive resource use still exists. By enabling optimal resource use and energy savings, disaggregation and micro-services were able to reduce the typical DC's up to 30%. Furthermore, we offer a heuristic to duplicate the Mixed integer model's output trends for energy-efficient allocation of caseloads in modularized DCs

Energy Efficient Placement of Workloads in Composable Data Center Networks

This paper studies the energy efficiency of composable datacentre (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