Achieving minimum bandwidth guarantees and work-conservation in large-scale, SDN-based datacenter networks

2017 ◽  
Vol 127 ◽  
pp. 109-125 ◽  
Author(s):  
Daniel S. Marcon ◽  
Fabrício M. Mazzola ◽  
Marinho P. Barcellos
Author(s):  
Tao Zhang ◽  
Yasi Lei ◽  
Qianqiang Zhang ◽  
Shaojun Zou ◽  
Juan Huang ◽  
...  

AbstractModern datacenters provide a wide variety of application services, which generate a mix of delay-sensitive short flows and throughput-oriented long flows, transmitting in the multi-path datacenter network. Though the existing load balancing designs successfully make full use of available parallel paths and attain high bisection network bandwidth, they reroute flows regardless of their dissimilar performance requirements. The short flows suffer from the problems of large queuing delay and packet reordering, while the long flows fail to obtain high throughput due to low link utilization and packet reordering. To address these inefficiency, we design a fine-grained load balancing scheme, namely TR (Traffic-aware Rerouting), which identifies flow types and executes flexible and traffic-aware rerouting to balance the performances of both short and long flows. Besides, to avoid packet reordering, TR leverages the reverse ACKs to estimate the switch-to-switch delay, thus excluding paths that potentially cause packet reordering. Moreover, TR is only deployed on the switch without any modification on end-hosts. The experimental results of large-scale NS2 simulations show that TR reduces the average and tail flow completion time for short flows by up to 60% and 80%, as well as provides up to 3.02x gain in throughput of long flows compared to the state-of-the-art load balancing schemes.


Author(s):  
Michael Galili ◽  
Valerija Kamchevska ◽  
Anna M. Fagertun ◽  
Sarah Ruepp ◽  
Michael S. Berger ◽  
...  

2020 ◽  
Vol 10 (21) ◽  
pp. 7874
Author(s):  
Shuo Wang ◽  
Zhiqiang Zhou ◽  
Hongjie Zhang ◽  
Jing Li

In the cloud datacenter, for the multi-tenant model, network resources should be fairly allocated among VDCs (virtual datacenters). Conventionally, the allocation of cloud network resources is on a best-effort basis, so the specific information of network resource allocation is unclear. Previous research has either aimed to provide minimum bandwidth guarantee, or focused on realizing work conservation according to the VM-to-VM (virtual machine to virtual machine) flow policy or per-source policy, or both policies. However, they failed to consider allocating redundant bandwidth among VDCs in a fair way. This paper presents a bandwidth that guarantees enforcement framework NXT-Freedom, and this framework allocates the network resources on the basis of per-VDC fairness, which can achieve work conservation. In order to guarantee per-VDC fair allocation, a hierarchical max–min fairness algorithm is put forward in this paper. In order to ensure that the framework can be applied to non-congestion-free network core and achieve scalability, NXT-Freedom decouples the computation of per-VDC allocation from the execution of allocation, but it brings some CPU overheads resulting from bandwidth enforcement. We observe that there is no need to enforce the non-blocking virtual network. Leveraging this observation, we distinguish the virtual network type of VDC to eliminate part of the CPU overheads. The evaluation results of a prototype prove that NXT-Freedom can achieve the isolation of per-VDC performance, which also shows fast adaption to flow variation in cloud datacenter.


2021 ◽  
Author(s):  
Tao Zhang ◽  
Yasi Lei ◽  
Qianqiang Zhang ◽  
Shaojun Zou ◽  
Juan Huang ◽  
...  

Abstract Modern datacenters provide a wide variety of application services, which generate a mix of delay-sensitive short flows and throughput-oriented long flows, transmitting in the multi-path datacenter network. Though the existing load balancing designs successfully make full use of available parallel paths and attain high bisection network bandwidth, they reroute flows regardless of their dissimilar performance requirements. The short flows suffer from the problems of large queuing delay and packet reordering, while the long flows fail to obtain high throughput due to low link utilization and packet reordering. To address these inefficiency, we design a fine-grained load balancing scheme, namely TR (Traffic-aware Rerouting), which identifies flow types and executes flexible and traffic-aware rerouting to balance the performances of both short and long flows. Besides, to avoid packet reordering, TR leverages the reverse ACKs to estimate the switch-to-switch delay, thus excluding paths that potentially cause packet reordering. Moreover, TR is only deployed on the switch without any modification on end-hosts. The experimental results of large-scale NS2 simulations show that TR reduces the average and tail flow completion time for short flows by up to 60% and 80%, as well as provides up to 3.02x gain in throughput of long flows compared to the state-of-the-art load balancing schemes.


2017 ◽  
Vol 124 ◽  
pp. 46-60 ◽  
Author(s):  
Lei Xu ◽  
Ke Xu ◽  
Yong Jiang ◽  
Fengyuan Ren ◽  
Haiyang Wang

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