Optimizing Flow Completion Time via Adaptive Buffer Management in Data Center Networks

Recently, with the increase in network bandwidth, various cloud computing applications have become popular. A large number of network data packets will be generated in such a network. However, most existing network architectures cannot effectively handle big data, thereby necessitating an efficient mechanism to reduce task completion time when large amounts of data are processed in data center networks. Unfortunately, achieving the minimum task completion time in the Hadoop system is an NP-complete problem. Although many studies have proposed schemes for improving network performance, they have shortcomings that degrade their performance. For this reason, in this study, we propose a centralized solution, called the bandwidth-aware rescheduling (BARE) mechanism for software-defined network (SDN)-based data center networks. BARE improves network performance by employing a prefetching mechanism and a centralized network monitor to collect global information, sorting out the locality data process, splitting tasks, and executing a rescheduling mechanism with a scheduler to reduce task completion time. Finally, we used simulations to demonstrate our scheme’s effectiveness. Simulation results show that our scheme outperforms other existing schemes in terms of task completion time and the ratio of data locality.

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Buffer Occupancy-Based Transport to Reduce Flow Completion Time of Short Flows in Data Center Networks

Symmetry ◽

10.3390/sym11050646 ◽

2019 ◽

Vol 11 (5) ◽

pp. 646 ◽

Cited By ~ 3

Author(s):

Hasnain Ahmed ◽

Muhammad Junaid Arshad

Keyword(s):

Congestion Control ◽

Data Center ◽

Completion Time ◽

Current Data ◽

Transport Protocol ◽

Transport Protocols ◽

Data Center Networks ◽

Buffer Occupancy ◽

Control Scheme ◽

Precise Measure

Today’s data centers host a variety of different applications that impose specific requirements for their flows. Applications that generate short flows are usually latency sensitive; they require their flows to be completed as fast as possible. Short flows suffer to quickly increase their sending rate due to the existing long flows occupying most of the available capacity. This problem is caused due to the slow convergence of the current data center transport protocols. In this paper, we present a buffer occupancy-based transport protocol (BOTCP) to reduce flow completion time of short flows. BOTCP consists of two parts: (i) A novel buffer occupancy-based congestion signal, and (ii) a congestion control scheme that uses the congestion signal to reduce flow completion time of short flows. The proposed buffer occupancy-based congestion signal gives a precise measure of congestion. The congestion control scheme makes a differentiated treatment of short and long flows to reduce flow completion time of short flows. The results show that BOTCP significantly improves flow completion time of short flows over the existing transport protocols in data center networks.

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Reducing Flow Completion Time with Replaceable Redundant Packets in Data Center Networks

2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS) ◽

10.1109/icdcs.2019.00014 ◽

2019 ◽

Author(s):

Sen Liu ◽

Jiawei Huang ◽

Wenchao Jiang ◽

Jianxin Wang ◽

Tian He

Keyword(s):

Data Center ◽

Completion Time ◽

Data Center Networks

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A Buffer Management Algorithm Based on Dynamic Marking Threshold to Restrain MicroBurst in Data Center Network

Information ◽

10.3390/info12090369 ◽

2021 ◽

Vol 12 (9) ◽

pp. 369

Author(s):

Yan Yu ◽

Xianliang Jiang ◽

Guang Jin ◽

Zihang Gao ◽

Penghui Li

Keyword(s):

Data Center ◽

Completion Time ◽

Buffer Management ◽

Network Simulator ◽

Design Load ◽

Control Information ◽

Management Algorithm ◽

Different Types ◽

The Face ◽

Business Flow

The data center has become the infrastructure of most Internet services, and its network carries different types of business flow, such as query, data backup, control information, etc. At the same time, the throughput-sensitive large flows occupy a lot of bandwidth, resulting in the small flow’s longer completion time, finally affecting the performance of the applications. Recent proposals consider only dynamically adjusting the ECN threshold or reversing the ECN packet priority. This paper combines these two improvements and presents the HDCQ method for coordinating data center queuing, separating large and small flows, and scheduling in order to ensure flow completion time. It uses the ECN mechanism to design load-adaptive marking threshold update algorithms for small flows to prevent micro-bursts from occurring. At the same time, packets marked with ECN or ACK are raised in priority, prompting these packets to be fed back to the sender as soon as possible, effectively reducing the TCP control loop delay. Extensive experimental analysis on the network simulator (NS-2) shows that the HDCQ algorithm has better performance in the face of micro-burst traffic, reducing the average flow completion time by up to 24% compared with the PIAS.

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Rethinking buffer management in data center networks

ACM SIGCOMM Computer Communication Review ◽

10.1145/2740070.2631462 ◽

2015 ◽

Vol 44 (4) ◽

pp. 575-576 ◽

Cited By ~ 1

Author(s):

Aisha Mushtaq ◽

Asad Khalid Ismail ◽

Abdul Wasay ◽

Bilal Mahmood ◽

Ihsan Ayyub Qazi ◽

...

Keyword(s):

Data Center ◽

Buffer Management ◽

Data Center Networks

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Class-based Flow Scheduling Framework in SDN-based Data Center Networks

10.36227/techrxiv.12927887 ◽

2020 ◽

Author(s):

Maiass Zaher ◽

Aymen Alawadi ◽

Sandor Molnar

Keyword(s):

Quality Of Service ◽

Data Center ◽

Completion Time ◽

Emerging Technologies ◽

Control Plane ◽

Traffic Patterns ◽

Data Center Networks ◽

Available Bandwidth

The emerging technologies leveraging Data Center Networks (DCN) and their consequent trafﬁc patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efﬁciently schedules ﬂows based on the available bandwidth to improve Flow Completion Time (FCT) of mice ﬂows. In addition, we propose a lightweight sampling mechanism to sample a portion of ﬂows. In particular, Sieve schedules the sampled ﬂows, and it reschedules only elephant ﬂows upon threshold hits. Furthermore, our framework allocates a portion of the ﬂows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.

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Class-based Flow Scheduling Framework in SDN-based Data Center Networks

10.36227/techrxiv.12927887.v1 ◽

2020 ◽

Author(s):

Maiass Zaher ◽

Aymen Alawadi ◽

Sandor Molnar

Keyword(s):

Quality Of Service ◽

Data Center ◽

Completion Time ◽

Emerging Technologies ◽

Control Plane ◽

Traffic Patterns ◽

Data Center Networks ◽

Available Bandwidth

The emerging technologies leveraging Data Center Networks (DCN) and their consequent trafﬁc patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efﬁciently schedules ﬂows based on the available bandwidth to improve Flow Completion Time (FCT) of mice ﬂows. In addition, we propose a lightweight sampling mechanism to sample a portion of ﬂows. In particular, Sieve schedules the sampled ﬂows, and it reschedules only elephant ﬂows upon threshold hits. Furthermore, our framework allocates a portion of the ﬂows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.

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