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

2019 ◽  
Author(s):  
Sen Liu ◽  
Jiawei Huang ◽  
Wenchao Jiang ◽  
Jianxin Wang ◽  
Tian He
Keyword(s):  
Data Center ◽  
Completion Time ◽  
Data Center Networks

scholarly journals Bandwidth-Aware Rescheduling Mechanism in SDN-Based Data Center Networks

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1774
Author(s):  
Ming-Chin Chuang ◽  
Chia-Cheng Yen ◽  
Chia-Jui Hung
Keyword(s):  
Data Center ◽  
Completion Time ◽  
Network Performance ◽  
Data Locality ◽  
Task Completion ◽  
Data Center Networks ◽  
Task Completion Time ◽  
Data Packets ◽  
Network Bandwidth ◽  
Data Process

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.

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

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 646 ◽  
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.

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

2021 ◽  
Author(s):  
Sen Liu ◽  
Xiang Lin ◽  
Zehua Guo ◽  
Yi Wang ◽  
Mohamed Adel Serhani ◽  
...  
Keyword(s):  
Data Center ◽  
Completion Time ◽  
Buffer Management ◽  
Data Center Networks

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

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.

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

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.

scholarly journals Packet-Based Load Balancing in Data Center Networks

2016 ◽  
Author(s):  
Yagiz Kaymak ◽  
Roberto Rojas-Cessa
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Completion Time ◽  
Transport Model ◽  
Data Center Networks ◽  
Order Problem ◽  
Packet Delivery ◽  
The Impact ◽  
Delay Difference ◽  
Single Path

In this paper, we evaluate the performance of packet-based load balancing in data center networks (DCNs). Throughput and flow completion time are some of the main the metrics considered to evaluate the performance of the transport of flows over the presence of long flows in a DCN. Load balancing in a DCN may improve those metrics but it may also generate out-of-order packet forwarding. Therefore, we investigate the impact of outof- order packet delivery on the throughput and flow completion time of long and short flows, respectively, in aDCN.We focus on per-packet load balancing. Our simulations show the presence of out-of-order packet delivery in a DCN using this load balancing approach. Simulation results also reveal that packetbased load balancing may yield smaller average flow completion time for short flows and larger average throughput for long flows than the single-path transport model used byTransmission Control Protocol (TCP), which prevents the presence of out-of-order packet delivery. Queueing diversity in the multipath structure of DCNs promotes susceptibility of out-of-order delivery. As the delay difference between alternative paths decreases, the occurrence of out-of-order packet delivery in packet-based load balancing also decreases. Therefore, under the studied scenarios, the benefits of the packet-based load balancing seem to outweigh the out-of-order problem.  

Analysis on Buffer Occupancy of Quantized Congestion Notification in Data Center Networks

2016 ◽  
Vol E99.B (11) ◽  
pp. 2361-2372 ◽  
Author(s):  
Chang RUAN ◽  
Jianxin WANG ◽  
Jiawei HUANG ◽  
Wanchun JIANG
Keyword(s):  
Data Center ◽  
Data Center Networks ◽  
Buffer Occupancy

scholarly journals HTPC: heterogeneous traffic-aware partition coding for random packet spraying in data center networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Shiqi Wang ◽  
Shuping Li ◽  
Shaojun Zou ◽  
Jinbin Hu ◽  
...  
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Network Performance ◽  
Rooted Tree ◽  
Heterogeneous Traffic ◽  
Data Center Networks ◽  
Packet Reordering ◽  
Traffic Characteristics ◽  
Network Utilization ◽  
The Impact

AbstractModern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

Sign in / Sign up

Export Citation Format

Share Document