Browsing by Author "Lee, Chain-Wu"

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An In-switch Rule Caching and Replacement Algorithm in Software Defined Networks
(2018-01-01)
Cheng, Tao
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Wang, Kuochen
;
Wang, Li-Chun
;
Lee, Chain-Wu
;
資訊工程學系
In the software defined networks (SDN), the flow table of an OpenFlow switch is usually implemented by the ternary content addressable memory (TCAM). The TCAM has limited capacity which may cause the flow table overflow problem. To address the problem, related works perform a rule replacement scheme according to either the estimated next-packet arrival time of each flow or the hit count of each rule; however, it may remove a rule whose packets will soon arrive at a switch, especially when the network is unstable. This paper proposes a novel TCAM management scheme named in-switch rule caching and replacement (IRCR) to better deal with the flow table overflow problem. The IRCR replaces a rule according to the expected number of incoming matched flows (EIMF), which can be derived from the inter-arrival time distribution models of the corresponding flows. The uniqueness of the IRCR is that it is designed as an in-switch application to avoid link delays between controllers and switches. Using either captured real network traffic or uniform distribution traffic, the IRCR outperforms related works for both exactly matched rules and wildcard rules in terms of hit ratios. In addition, the IRCR has little overhead to the switch.
Heterogeneous Flow Table Integration for Capacity Enhancement in Software-Defined Networks
(2018-01-01)
Hung, Chi-Hsiang
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Wang, Jheng-Jyun
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Wang, Li-Chun
;
Wang, Kuo-Chen
;
Lee, Chain-Wu
Commercial OpenFlow-enabled legacy switches implement flow tables with Ternary Content Addressable Memory (TCAM) to perform high speed flow matching process. However, the size of TCAM-based flow table is restricted to few thousands of entries due to manufacturing cost and high power consumption. In this paper, we propose the Flow Entry Agent which can integrate heterogeneous flow tables, such as ASIC-side MAC/IP/ACL tables and CPU-side SRAM-based tables to increase the storage capacity without modifying ASIC. Besides, the Agent will compress the CPU-side tables and perform flow matching process with these tables. Simulation results show that our Agent can not only increase the capacity of flow table to 11.38x to 65.24x but also reduce 80.99% to 87.36% of Packet_In messages with additional 1 MB CPU-side SRAM.
High-Efficiency Matching Mechanism for Off-Chip Tables in OpenFlow-enabled Legacy Switch
(2017-01-01)
Wang, Jheng-Jyun
;
Hung, Chi-Hsiang
;
Wang, Li-Chun
;
Wang, Kuo-Chen
;
Lee, Chain-Wu
Commercial OpenFlow-enabled legacy switches implement flow tables with Ternary Content Addressable Memory (TCAM) to perform high-speed flow matching process. However, the size of TCAM-based flow table is restricted to few thousands of entries due to manufacturing cost and high power consumption. In our previous research, we proposed Flow Entry Agent to integrate Off-Chip tables to increase the storage capacity without modifying Application Specific Integrated Circuit (ASIC). In this paper, we propose an efficient matching mechanism for Off-Chip tables. Simulation results show that our mechanism significantly increase the efficiency of flow matching process.
In-switch Dynamic Flow Aggregation in Software Defined Networks
(2017-01-01)
Chao, Tzu-Yu
;
Wang, Kuochen
;
Wang, Lichun
;
Lee, Chain-Wu
;
資訊工程學系
The limited size of the flow table, usually implemented by ternary content addressable memory (TCAM), may result in the flow table overflow problem, which becomes severer in software defined networks (SDN). To conquer this problem, this paper proposes an in-switch dynamic flow aggregation (IDFA) mechanism, which can be dynamically triggered. In the IDFA, redundant flow entries are inserted to speed up flow aggregation convergence time. The uniqueness of the proposed IDFA is that it resides in an OpenFlow switch, instead of acting as an application in an SDN controller, which avoids link delays between the controller and switches. This paper also proposes two novel techniques, degradation and repermutation, to aggregate flows effectively while keeping semantic equivalence. Evaluation results show that, the average compression ratio of the IDFA in a fat-tree topology under a LAN (random IP) environment is 26.3% (43%) better than that of the Flow Table Reduction Scheme (FTRS), a representative related work. The average flow aggregation convergence time of the IDFA in the fat-tree topology is 84% shorter than that of the FTRS. In addition, the occurrence probability of flow table overflow in the fat-tree topology is 26.71% lower than that of the FTRS.