Cross-Examination of Datacenter Workload Modeling Techniques

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Provided by: Stanford Technology Ventures Program
Topic: Big Data
Format: PDF
Datacenter workload modeling has become a necessity in recent years due to the emergence of large-scale applications and cloud data-stores, whose implementation remains largely unknown. Detailed knowledge of target workloads is critical in order to correctly provision performance, power and cost-optimized systems. In this paper, the authors aggregate previous work on datacenter workload modeling and perform a qualitative comparison based on the representativeness, accuracy and completeness of these designs. They categorize modeling techniques in two main approaches, in-breadth and in-depth, based on the way they address the modeling of the workload.
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