Link Load Correlation-Based Blocking Performance Analysis for Tree-Type Data Center Networks
Source abstract
Abstract
With the explosive growth of cloud computing applications, the east-west traffic among servers has come to occupy the dominant proportion of the traffic in data center networks (DCNs). Cloud computing tasks need to be executed in a distributed manner on multiple servers, which exchange large amounts of intermediate data between the adjacent stages of each multi-stage task. Therefore, the congestion in DCNs can reduce the processing performance when conducting multi-stage tasks. To address this, the relationship between the blocking performance and the traffic load can be adopted as a theoretical basis for network planning and traffic engineering. In this paper, the traffic load correlation between edge links and aggregation links is considered, and an iterative blocking performance analysis method is proposed for two-layer tree-type DCNs. The simulation results show the good accuracy of the proposed method with respect to the theoretical results especially in the blocking rate range below 4% and with over-subscription ratio 1.5.
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Research context
OpenAlex topics: Software-Defined Networks and 5G · Cloud Computing and Resource Management · Advanced Optical Network Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071, China
Guangzhou Institute of Technology, Xidian University, Guangzhou 510555, China
School of Software, Northwestern Polytechnical University, Xi’an 710071, China
Funding
National Natural Science Foundation of China · Guangdong Basic and Applied Basic Research Foundation
References (29)
Show source-provided references
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