Improved Solution to TCP Incast Problem in Data Center Networks

Chen, Kai; Zheng, Hongyun; Zhao, Yongqiang; Guo, Yuchun

doi:10.1109/cyberc.2012.78

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…They further reported that TCP slow start failed tackling Incast. Another attempt is done by Chen et al [16], where authors proposed limited number of senders to handle Incast. Although, it solves the problem.…”

Section: Related Work a Incast In Traditional Storage Systemsmentioning

confidence: 99%

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Incast Mitigation in a Data Center Storage Cluster Through a Dynamic Fair-Share Buffer Policy

et al. 2019

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Incast is a phenomenon when multiple devices interact with only one device at a given time. Multiple storage senders overflow either the switch buffer or the single-receiver memory. This pattern causes all concurrent-senders to stop and wait for buffer/memory availability, and leads to a packet loss and retransmission-resulting in a huge latency. We present a software-defined technique tackling the manyto-one communication pattern-Incast-in a data center storage cluster. Our proposed method decouples the default TCP windowing mechanism from all storage servers, and delegates it to the software-defined storage controller. The proposed method removes the TCP saw-tooth behavior, provides a global flow awareness, and implements the dynamic fair-share buffer policy for end-to-end I/O path. It considers all I/O stages (applications, device drivers, NICs, switches/routers, file systems, I/O schedulers, main memory, and physical disks) while achieving the maximum I/O throughput. The policy, which is part of the proposed method, allocates fair-share bandwidth utilization for all storage servers. Priority queues are incorporated to handle the most important data flows. In addition, the proposed method provides better manageability and maintainability compared with traditional storage networks, where data plane and control plane reside in the same device. INDEX TERMS Incast, software-defined storage, I/O throughput, dynamic fair-share buffer, end-to-end I/O path, fair-share BW utilization.

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Section: Related Work a Incast In Traditional Storage Systemsmentioning

confidence: 99%

“…Chen et al [16] limited the number of concurrent sender to mitigate Incast. We should find a better solution for concurrent senders to help the scalability factor of storage system.…”

Section: Anatomy Of Incastmentioning

confidence: 99%

Incast Mitigation in a Data Center Storage Cluster Through a Dynamic Fair-Share Buffer Policy

et al. 2019

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“…The large latency caused by incast congestion has been widely investigated [1]- [7]. In the high capacity DCN, when multiple servers respond to one client, highly bursty data overfill the scarce switch buffer immediately.…”

Section: Introductionmentioning

confidence: 99%

MIP: Minimizing the idle period of data transmission in data center networks

Deng

Wang

2014

2014 IEEE International Conference on Communications (ICC)

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In today's data center networks, incast congestion happens when multiple servers send data to one receiver simultaneously. Such congestion results in long idle periods of transmission, which significantly delays the mission complete time (MCT). In this paper, we introduce the MIP, a simple distributed scheme at sender side to Minimize the Idle Periods. To this end, MIP increases the concurrency of data transmission by using proactive fair rate control and cut down idle period further by carefully selected RT O. Extensive simulations show that MIP is able to provide near-optimal MCT performance. In particular, MIP requires no modification to OS kernel or switches in current data center networks.

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Optimizing data center network throughput by solving TCP Incast problem using k‐means algorithm

Thiruvenkatam

Mukeshkrishnan

2020

Int J Communication

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SummaryTCP in casting referred to as one of the complex problems in the data center, which receives a huge amount of traffic volume from n number of senders. There are many methods proposed to solve the TCP Incast problem. In this paper, there are two steps proposed: (i) grouping sender nodes using the k‐means algorithm and (ii) handling incoming packets from the senders after grouping. Grouping senders make it easy to handle the incoming packets effectively as the complexity reduces reasonably. This is achieved through the k‐means algorithm that groups the senders and makes a priority queue for each group. The second step can be achieved through Pro‐Ack (Pro‐Acknowledgement) control in one of the methods for handling a huge volume of data at the receiver side. We demonstrated how the incoming packets can be processed and handled effectively through Pro‐Ack control with the help of the k‐means algorithm. Along with the above concepts, the robust algorithm is proposed to make priority queues. The input throughput also out performs with the existing algorithms.

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Improved Solution to TCP Incast Problem in Data Center Networks

Cited by 4 publications

References 13 publications

Incast Mitigation in a Data Center Storage Cluster Through a Dynamic Fair-Share Buffer Policy

Incast Mitigation in a Data Center Storage Cluster Through a Dynamic Fair-Share Buffer Policy

MIP: Minimizing the idle period of data transmission in data center networks

Optimizing data center network throughput by solving TCP Incast problem using k‐means algorithm

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