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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Huang, Ching-ChunSubject: search.filters.subject.P4

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Now showing 1 - 3 of 3
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    SDN Soft Computing Application for Detecting Heavy Hitters
    (2019-10-01)
    Lin, Yi-Bing
    ;
    Huang, Ching-Chun
    ;
    Tsai, Shi-Chun
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    資訊工程學系
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    Department of Computer Science
    To avoid distributed denial-of-service (DDoS) attacks or real-time transmission control protocol (TCP) incast in the software-defined networking (SDN) environment, the HashPipe algorithm was developed following the space-saving approach. Unfortunately, HashPipe implemented in the behavioral model (bmv2) cannot be directly executed at a real programming protocol-independent packet processor (P4) switch due to P4 pipeline limitation. Based on the Banzai machine model, this paper shows how to smartly utilize the Banzai atoms to develop HashPipe as a soft computing application in a real P4 switch. Then we propose an enhanced HashPipe algorithm that significantly improves the accuracy of the original HashPipe. The proposed heavy hitter detection is executed at the line-rate of the Tofino P4 switch with the highest process rate in the world.
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    High-speed data-plane packet aggregation and disaggregation by P4 switches
    (2019-09-15)
    Wang, Shie-Yuan
    ;
    Wu, Chia-Ming
    ;
    Lin, Yi-Bing
    ;
    Huang, Ching-Chun
    ;
    資訊工程學系
    In this paper, we propose novel approaches that utilize the header manipulations of the P4 (Programming Protocol-Independent Packet Processor) switches to aggregate small IoT packets into a large one, transmit it over a network, and then disaggregate it back to the original small packets, all in the data plane of the hardware P4 switch to provide high throughputs. Packet aggregation and disaggregation provide many important benefits and have been proposed and performed in the past. However, most existing approaches perform packet aggregation and disaggregation in the control plane either by the switch CPU or by the server CPU, resulting in low throughputs. Our work is the first work that designs and implements packet aggregation and disaggregation purely in the pipelines of the switching ASIC. In this paper, we present the design and implementation of our approaches, their measured throughputs, and the insights that we have obtained from this pioneering work.
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    The SDN Approach for the Aggregation/Disaggregation of Sensor Data
    (2018-07-01)
    Lin, Yi-Bing
    ;
    Wang, Shie-Yuan
    ;
    Huang, Ching-Chun
    ;
    Wu, Chia-Ming
    ;
    資訊工程學系
    In many Internet of Things (IoT) applications, large numbers of small sensor data are delivered in the network, which may cause heavy traffics. To reduce the number of messages delivered from the sensor devices to the IoT server, a promising approach is to aggregate several small IoT messages into a large packet before they are delivered through the network. When the packets arrive at the destination, they are disaggregated into the original IoT messages. In the existing solutions, packet aggregation/disaggregation is performed by software at the server, which results in long delays and low throughputs. To resolve the above issue, this paper utilizes the programmable Software Defined Networking (SDN) switch to program quick packet aggregation and disaggregation. Specifically, we consider the Programming Protocol-Independent Packet Processor (P4) technology. We design and develop novel P4 programs for aggregation and disaggregation in commercial P4 switches. Our study indicates that packet aggregation can be achieved in a P4 switch with its line rate (without extra packet processing cost). On the other hand, to disaggregate a packet that combines N IoT messages, the processing time is about the same as processing N individual IoT messages. Our implementation conducts IoT message aggregation at the highest bit rate (100 Gbps) that has not been found in the literature. We further propose to provide a small buffer in the P4 switch to significantly reduce the processing power for disaggregating a packet.