CSR: Small: High-Fidelity Datacenter Emulation

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This research addresses a fundamental computer systems challenge presented by the rise of datacenter computing as the dominant platform for ``cloud computing.'' Today, datacenters host mission-critical services for IT, health, and financial institutions using complex systems consisting of large ensembles of machines spread across multiple physical networks and geographic regions. These sophisticated services must meet stringent design and performance requirements such as horizontal scalability, fault tolerance, self adaptation, and security while leveraging low-cost commodity hardware. A key challenge is to quantify the impact of hardware changes, software designs, and energy management policies. Critically, such evaluations require the real code, workloads, component interactions, heterogeneous hardware, and high-load conditions to accurately predict performance. This proposal investigates techniques and architectures for building a high-fidelity datacenter emulation platform to transform datacenter network and service design from a black art into a rigorous, accurate, and repeatable (scientific) process. Such a facility allows researchers and architects to develop the principles and best practices for next-generation datacenter design. By accurately emulating realistic datacenter scales (10,000+ machines, 100+switches, multiple cooperating services) with a modest cluster of a few hundred machines, the proposed work aims to place datacenter experimentation within the reach of students, academics, and businesses without the financial reach of large IT firms.