PROJECT TITLE :

Adaptive Path Isolation for Elephant and Mice Flows by Exploiting Path Diversity in Datacenters

ABSTRACT:

Resource competition and conflicts in datacenter networks (DCNs) are frequent and intense. They become inevitable when mixing elephant and mice flows on shared transmission paths, ensuing in arbitration between throughput and latency and performance degradation. We tend to propose a unique flow scheduling theme, Freeway, that leverages on path diversity within the DCN topology to ensure, simultaneously, mice flow completion at intervals deadline and high network utilization. Freeway adaptively partitions the offered paths into low latency and high throughput paths and provides different transmission services for each class. A M/G/1-based mostly model is developed to theoretically obtain the highest price of average delay over the trail that will guarantee for ninety ninep.c of mice flows their completion time before the deadline. Based mostly on this certain, Freeway proposes a dynamic path partitioning algorithm to adjust dynamically with varying traffic load the amount of low latency and high throughput methods. While mice flows are transmitted over low latency methods using a simple equal price multiple path (ECMP) scheduling, Freeway load balances elephant flows on totally different high-throughput ways. We evaluate Freeway in an exceedingly series of simulation on a massive scale topology and use real traces. Our evaluation results show that Freeway considerably reduces the mice flows completion time within deadlines, while achieving remarkable throughput compared with current schemes. It's exceptional that Freeway will not would like any change of DCN switch materials or scheduling algorithms and can be deployed easily on any generic datacenter network with switches implementing VLANs and trunking.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Adaptive Pulse Wave Imaging Automated Spatial Vessel Wall Inhomogeneity Detection in Phantoms and in-Vivo ABSTRACT: Imaging the mechanical characteristics of the artery wall may aid in the diagnosis of vascular
PROJECT TITLE : An Adaptive and Robust Edge Detection Method Based on Edge Proportion Statistics ABSTRACT: One of the most important preprocessing steps for high-level tasks in the field of image analysis and computer vision is
PROJECT TITLE : Learned Image Downscaling for Upscaling Using Content Adaptive Resampler ABSTRACT: SR models based on deep convolutional neural networks have shown greater performance in recovering the underlying high-resolution
PROJECT TITLE : Multipatch Unbiased Distance Non-Local Adaptive Means With Wavelet Shrinkage ABSTRACT: Many existing non-local means (NLM) approaches either utilise Euclidean distance to quantify the similarity between patches,
PROJECT TITLE : Depth Restoration From RGB-D Data via Joint Adaptive Regularization and Thresholding on Manifolds ABSTRACT: By integrating the properties of local and non-local manifolds that offer low-dimensional parameterizations

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry