Heterogeneous Flow Table Distribution in Software-defined Networks
碩士 === 國立中央大學 === 資訊工程學系 === 103 === Recently, Software-defined Network (SDN) has become an important and popular technology which provides for the flexibility of developing new protocols and the policies of real networks. The controller in SDN translates network policies into rules which are instal...
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ndltd-TW-103NCU053920222019-10-24T05:19:19Z http://ndltd.ncl.edu.tw/handle/yzd7s5 Heterogeneous Flow Table Distribution in Software-defined Networks Chun-Feng Wang 王竣鋒 碩士 國立中央大學 資訊工程學系 103 Recently, Software-defined Network (SDN) has become an important and popular technology which provides for the flexibility of developing new protocols and the policies of real networks. The controller in SDN translates network policies into rules which are installed in the flow tables (Flow tables are usually stored in ternary content addressable memory (TCAM)) of switches in the networks. Hence, TCAM usually has some critical disadvantages (e.g., high costs, power consumption and high heat generation). Flow tables cannot scale beyond a few hundred entries. Therefore, switches may need to cache rules reactively (i.e., installing rules on demand). However, when cache misses happen, switches will send the packet-in message to the controller and reactively cache the rules, which causes packet delay and large buffers. In this thesis, we propose a rule partition and allocation algorithm that distributes rules across network switches to improve the performance. Our algorithm not only is applicable to small TCAM switch scenario, but also guarantees semantically-invariant (i.e., the global action of the network is unchanged). We implement our algorithm into the real world SDN scenario and the experiment result shows that our algorithm have obviously reduced TCAM usage. Guey-Yun Chang 張貴雲 2015 學位論文 ; thesis 89 en_US |
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碩士 === 國立中央大學 === 資訊工程學系 === 103 === Recently, Software-defined Network (SDN) has become an important and popular technology which provides for the flexibility of developing new protocols and the policies of real networks. The controller in SDN translates network policies into rules which are installed in the flow tables (Flow tables are usually stored in ternary content addressable memory (TCAM)) of switches in the networks. Hence, TCAM usually has some critical disadvantages (e.g., high costs, power consumption and high heat generation). Flow tables cannot scale beyond a few hundred entries. Therefore, switches may need to cache rules reactively (i.e., installing rules on demand). However, when cache misses happen, switches will send the packet-in message to the controller and reactively cache the rules, which causes packet delay and large buffers. In this thesis, we propose a rule partition and allocation algorithm that distributes rules across network switches to improve the performance. Our algorithm not only is applicable to small TCAM switch scenario, but also guarantees semantically-invariant (i.e., the global action of the network is unchanged). We implement our algorithm into the real world SDN scenario and the experiment result shows that our algorithm have obviously reduced TCAM usage.
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Guey-Yun Chang |
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Guey-Yun Chang Chun-Feng Wang 王竣鋒 |
author |
Chun-Feng Wang 王竣鋒 |
spellingShingle |
Chun-Feng Wang 王竣鋒 Heterogeneous Flow Table Distribution in Software-defined Networks |
author_sort |
Chun-Feng Wang |
title |
Heterogeneous Flow Table Distribution in Software-defined Networks |
title_short |
Heterogeneous Flow Table Distribution in Software-defined Networks |
title_full |
Heterogeneous Flow Table Distribution in Software-defined Networks |
title_fullStr |
Heterogeneous Flow Table Distribution in Software-defined Networks |
title_full_unstemmed |
Heterogeneous Flow Table Distribution in Software-defined Networks |
title_sort |
heterogeneous flow table distribution in software-defined networks |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/yzd7s5 |
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AT chunfengwang heterogeneousflowtabledistributioninsoftwaredefinednetworks AT wángjùnfēng heterogeneousflowtabledistributioninsoftwaredefinednetworks |
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1719276682522656768 |