Lightweight Flow Distribution for Collaborative Traffic Measurement in Software Defined Networks
| Autor: | Shigang Chen, Hongli Xu, Qianpiao Ma, Liusheng Huang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Optimization problem
Computer science Flow distribution 020204 information systems Control system Distributed computing 0202 electrical engineering electronic engineering information engineering Forwarding plane 020206 networking & telecommunications 02 engineering and technology Load balancing (computing) Routing control plane Software-defined networking |
| Zdroj: | INFOCOM |
| DOI: | 10.1109/infocom.2019.8737516 |
| Popis: | Many important functions in software defined networks can benefit from fine-grained traffic measurement at flow level. Because TCAM-based flow entries only provide aggregate traffic statistics, prior research has suggested to perform flow-level measurement in SRAM and balance the measurement load across the network through collaborative traffic measurement. The key problem of collaborative measurement is to provide a mechanism to distribute flows to switches such that each switch can identify its subset of flows to measure. We observe that the prior work has focused on optimizing flow distribution among switches, but overlooked their high space and per-packet processing overhead introduced to the data plane, which becomes a serious issue in large SDN systems. In this paper, we propose a new lightweight solution to the flow distribution problem. It follows the design principle of alleviating complexity of the data plane by minimizing the data-plane space and processing overhead. At the control plane, we formulate flow distribution as optimization problems under two scenarios that implement collaborative measurement by edge switches only and by edge/core switches together, respectively. Our extensive simulations demonstrate that, comparing with the best existing work, the proposed lightweight solution achieves a comparable performance in terms of load balancing, while drastically reducing both space overhead and per-packet processing overhead, making it more practical in real-world systems that are sensitive to the additional overhead introduced by flow distribution. |
| Databáze: | OpenAIRE |
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