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Multi-Tenancy- and Redundancy-Aware In-Network Aggregation using Programmable Switches

delete2023-05-01
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PRE
AI
S
Sol Han
H
Hochan Lee
S
Subin Han
H
Heewon Kim
S
Sangheon Pack *
DOI:10.1109/MNET.107.2100635delete
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摘要

摘要

En 中文
Recent advances in programmable switches make it possible to aggregate data in partition-aggregation applications (e.g., MapReduce applications) at programmable switches. However, a well-designed aggregation scheme is indispensable for aggregating as much data as possible under the limited resources of programmable switches in an environment where multiple applications are running concurrently. In this article, we propose a multi-tenancy and redundancy-aware in-network aggregation (MARINA) scheme that preferentially aggregates highly redundant data at a programmable switch and improves aggregation performance by constructing a multi-tenancy-aware aggregation tree. Evaluation results demonstrate that MARINA can improve data aggregation performance by up to 81 percent compared with the conventional approach using statically partitioned resources and sequential aggregation.
Keyword:
Data aggregation
Steiner trees
Servers
Switches
Random access memory
Aggregates
Memory management

期刊

IEEE Network 封面图
IEEE Network
IF:
6.3
论文数:
2.7K
被引数:
1.1W

机构

K
Korea University
学者数:
3.6W
论文数: 3.8W
被引数: 4.4W
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