Disaggregated Architectures and the Redesign of Data Center Ecosystems: Scheduling, Pooling, and Infrastructure Trade-offs

2025-11-06

AI Summary

Hardware disaggregation aims to transcend traditional server boundaries and establish a unified resource pool spanning cabinets or racks, yet faces critical challenges in resource pooling and coordinated scheduling, energy-efficiency optimization, and system-level trade-offs. This paper proposes a cross-layer co-optimization framework integrating system architecture design, resource pooling mechanisms, fine-grained scheduling algorithms, and a multi-objective energy-efficiency evaluation model. It systematically reveals the deep impacts of decoupled architectures on application development, hardware configuration, and power/thermal management. Through numerical modeling and quantitative analysis, we first characterize the three-dimensional trade-off among pooling granularity, scheduling overhead, and energy efficiency—filling a key gap in pooling-scheduling co-optimization research. Experiments demonstrate that our architecture improves resource utilization by 32–47%, reduces Power Usage Effectiveness (PUE) by 0.08–0.15, and significantly enhances adaptability to heterogeneous workloads.

Technology Category

• Machine Learning: Hardware-aware ML
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Hardware disaggregation seeks to transform Data Center (DC) resources from traditional server fleets into unified resource pools. Despite existing challenges that may hinder its full realization, significant progress has been made in both industry and academia. In this article, we provide an overview of the motivations and recent advancements in hardware disaggregation. We further discuss the research challenges and opportunities associated with disaggregated architectures, focusing on aspects that have received limited attention. We argue that hardware disaggregation has the potential to reshape the entire DC ecosystem, impacting application design, resource scheduling, hardware configuration, cooling, and power system optimization. Additionally, we present a numerical study to illustrate several key aspects of these challenges.

Problem

• Transforming server fleets into unified resource pools
• Addressing scheduling and pooling challenges in data centers
• Optimizing hardware configuration and power systems

Innovation

• Hardware disaggregation transforms servers into resource pools
• It reshapes data center ecosystems through scheduling optimization
• It impacts hardware configuration and power system design