On the Performance of a Large-Scale Optical Packet Switch Under Realistic Data Center Traffic

2013 ◽  
Vol 5 (6) ◽  
pp. 565 ◽  
Author(s):  
Nicola Calabretta ◽  
Roger Pueyo Centelles ◽  
Stefano Di Lucente ◽  
Harmen J. S. Dorren
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Optical Packet Switch ◽  
Packet Switch ◽  
Realistic Data

Optical Switching in Next-Generation Data Centers

2019 ◽  
pp. 164-193 ◽  
Author(s):  
Vaibhav Shukla ◽  
Rajiv Srivastava ◽  
Dilip Kumar Choubey
Keyword(s):  
Data Center ◽  
Optical Switching ◽  
Large Scale ◽  
Data Centers ◽  
Current Data ◽  
Limited Bandwidth ◽  
Switch Architectures ◽  
Pros And Cons ◽  
High Power Consumption ◽  
Packet Switch

The leading content provider companies like Google, Yahoo, and Amazon installed mega-data centers that contain hundreds of thousands of servers in very large scale. The current data center systems are organized in the form of the hierarchal tree structure based on bandwidth-limited electronic switches. Modern data center systems face a number of issues like high power consumption, limited bandwidth availability, server connectivity, energy and cost efficiency, traffic complexity, etc. One of the most feasible solution of these issues is the use of optical switching technologies in the core of data center systems. In this chapter a brief description about the modern data center system is presented, and some prominent optical packet switch architectures are also presented in this chapter with their pros and cons.

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.

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