Packet Reordering in Geneve Overlay Network
draft-yu-nvo3-geneve-pkt-reordering-00

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INTERNET-DRAFT                                                     Y. Yu
Intended Status: Standards Track                     Huawei Technologies
Expires: Mar 5, 2019                                             J. Wang
                                                           China Telecom
                                                             Sep 1, 2018

              Packet Reordering in Geneve Overlay Network
               draft-yu-nvo3-geneve-pkt-reordering-00

Abstract

   Congestion is the killer of low latency and high throughput.Network
   congestion occurs on the interconnection links of a data center due
   to poor traffic distribution. Load balancing technologies are used to
   solve network congestion. Packet spraying is a kind of load balancing
   technology with finer granularity. During this situation, the packets
   may arrive at the destination out of order.  This document describes
   a reordering protocol in the Geneve encapsulation network[1] using a
   newly defined Geneve Option field.

Status of this Memo

   This Internet-Draft is submitted to IETF in full conformance with the
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Copyright and License Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors. All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   described in the Simplified BSD License.

Table of Contents

   1  Introduction  . . . . . . . . . . . . . . . . . . . . . . . . .  3
   2  Terminology . . . . . . . . . . . . . . . . . . . . . . . . . .  3
   3  Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . .  3
   4  Problem Statements & Requirements . . . . . . . . . . . . . . .  3
   5  Packet Reordering on Geneve . . . . . . . . . . . . . . . . . .  4
     5.1 Packet Reordering Format . . . . . . . . . . . . . . . . . .  4
     5.2 Packet Reordering Capability Discovery . . . . . . . . . . .  6
   6  Security Considerations . . . . . . . . . . . . . . . . . . . .  8
   7  IANA Considerations . . . . . . . . . . . . . . . . . . . . . .  8
   8  References  . . . . . . . . . . . . . . . . . . . . . . . . . .  8
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . .  9

 

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1  Introduction

   In many current data centers, network utilization is not has high as
   it could be. For example, in some scenarios, the average network
   utilization is about 20% and the peak utilization is about 45%[2].
   With the improvement of end systems (or endpoints), the  deployment
   of multi-services and high-volume traffic services (such as streaming
   media, big data processing applications and user-oriented large-scale
   web applications, etc.), more and more network performance problems
   appear. These problems are created by traffic bursts and traffic
   routing collisions. The imbalance of traffic on the network becomes
   more and more prominent which leads to underutilized network
   bandwidth and decreased overall performance of network applications.

   In order to fully utilize the available network bandwidth, traffic
   flows into the network are dispersed across multiple paths to achieve
   load balancing. The finer the granularity of the load balancing, the
   higher the utilization of available network bandwidth. Current flow-
   based and flowlet-based[3] approaches are more coarse grain than
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