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Expressive Content-Based Routing in Software-Defined Networks

delete2018-11-01
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S
Sukanya Bhowmik *
M
Muhammad Adnan Tariq
K
Kurt Rothermel
DOI:10.1109/TPDS.2018.2840698delete
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摘要

摘要

En 中文
With the vision of Internet of Things gaining popularity at a global level, efficient publish/subscribe middleware for communication within and across data centers is extremely desirable. In this respect, the very popular Software-Defined Networking, which enables publish/subscribe middleware to perform line-rate filtering of events directly on hardware, can prove to be very useful. While deploying content filters directly on switches of a software-defined network allows optimized paths, high throughput rates, and low end-to-end latency, it suffers from certain inherent limitations with respect to number of bits available on hardware switches to represent these filters. Such a limitation affects expressiveness of filters, resulting in unnecessary traffic in the network. In this paper, we explore various complementary techniques to represent content filters expressively while being limited by hardware. We implement and evaluate techniques that i) use workload, in terms of events and subscriptions, to represent content, and ii) efficiently select attributes to reduce redundancy in content. Our detailed performance evaluations show the potential of these techniques in reducing unnecessary traffic when subjected to different workloads. Furthermore, the techniques proposed in this paper require significant updates to the network, i.e., the data plane, which must be performed in a consistent manner to ensure desired system behavior. As a result, in this paper, we, also, design and evaluate a light-weight approach that ensures data plane consistency in the presence of dynamic network updates.
Keyword:
Content-based routing
software-defined networking
bandwidth efficiency
hardware limitations
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期刊

IEEE Transactions on Parallel and Distributed Systems 封面图
IEEE Transactions on Parallel and Distributed Systems
IF:
6
论文数:
5.2K
被引数:
1.1W

机构

U
University of Stuttgart
学者数:
1.1W
论文数: 9.4K
被引数: 1.3W
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