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An early congestion feedback and rate adjustment schemes for many-to-one communication in cloud-based data center networks

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Abstract

Cloud data centers are playing an important role for providing many online services such as web search, cloud computing and back-end computations such as MapReduce and BigTable. In data center network, there are three basic requirements for the data center transport protocol such as high throughput, low latency and high burst tolerance. Unfortunately, conventional TCP protocols are unable to meet the requirements of data center transport protocol. One of the main practical issues of great importance is TCP Incast to occur many-to-one communication sessions in data centers, in which TCP experiences sharp degradation of throughput and higher delay. This important issue in data center networks has already attracted the researchers because of the development of cloud computing. Recently, few solutions have been proposed for improving the performance of TCP in data center networks. Among that, DCTCP is the most popular protocol in academic as well as industry areas due to its better performance in terms of throughput and latency. Although DCTCP provides significant performance improvements, there are still some defects in maintaining the queue length and throughput when the number of servers is too large. To address this problem, we propose a simple and efficient TCP protocol, namely NewDCTCP as an improvement of DCTCP in data center networks. NewDCTCP modified the congestion feedback and window adjusting schemes of DCTCP to mitigate the TCP Incast problem. Through detailed QualNet experiments, we show that NewDCTCP significantly outperforms DCTCP and TCP in terms of goodput and latency. The experimental results also demonstrate that NewDCTCP flows provide better link efficiency and fairness with respect to DCTCP.

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Acknowledgments

The authors gratefully acknowledge the anonymous reviewers for their valuable comments and suggestions for improving the manuscript. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2011- 0023177) and the ICT R&D program of MSIP/IITP (B0126-15-1051, A study on Hyper Connected Self-Organizing Network Infrastructure Technologies for IoT Service) and MSIP/IITP (12221-14-1005, Software Platform for ICT Equipments).

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Authors and Affiliations

  1. Department of Electronics and Computer Engineering, Hanyang University, Seoul, South Korea

    Prasanthi Sreekumari & Jae-il Jung

  2. Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea

    Meejeong Lee

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  1. Prasanthi Sreekumari
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Correspondence to Meejeong Lee.

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Sreekumari, P., Jung, Ji. & Lee, M. An early congestion feedback and rate adjustment schemes for many-to-one communication in cloud-based data center networks. Photon Netw Commun 31, 23–35 (2016). https://doi.org/10.1007/s11107-015-0526-y

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