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Tensor-Based Rule-Space Management System in SDN

delete2019-12-01
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PRE
AI
I
Ilora Maity
A
Ayan Mondal
S
Sudip Misra *
C
Chittaranjan Mandal
DOI:10.1109/JSYST.2018.2879321delete
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摘要

摘要

En 中文
This paper presents a tensor-based rule-space management (TERM) system for improving the available capacity of switches in software defined networking (SDN). Limited storage capacity of switches is a key challenge in SDN as the switches use ternary content addressable memories having very low capacity. Low rule storage capacity eventually leads to the high number of Packet-In messages and control plane overloading. The challenge is to design a dynamic scheme to store a large number of heterogeneous flow-rules in SDN switches and reduce the number of Packet-In messages. To address this problem, we apply the concept of tensor decomposition in order to aggregate flow-rules. In addition, we employ a rule caching mechanism for better throughput. Simulation results show the efficiency of TERM in terms of reduction in the number of Packet-In messages. TERM reduces the Packet-In message count by 57.78% than the flow aggregation approach proposed in the existing literature.
Keyword:
Caching
flow-rule
software defined networking (SDN)
ternary content addressable memories (TCAM)
tensor decomposition
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期刊

I
IEEE Open Journal of Circuits and Systems
IF:
2.4
论文数:
4.5K
被引数:
387

机构

I
indian institute of technology system (iit system)
学者数:
9.5W
论文数: 9.9W
被引数: 93
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