Home>Results

  • Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

[期刊论文]

Elastically Scaling Control Channels in Network Measurement With Escala

Share
Edit Delete 报错

author:

Liu, Hongyan (Liu, Hongyan.) [1] | Chen, Xiang (Chen, Xiang.) [2] | Huang, Qun (Huang, Qun.) [3] | Unfold

Indexed by:

Scopus SCIE

Abstract:

In network measurement, data plane switches measure traffic and report events (e.g., heavy hitters) to the control plane via control channels. The control plane makes decisions to process events. However, current network measurement suffers from two problems. First, when traffic bursts occur, massive events are reported in a short time so that the control channels may be overloaded due to limited bandwidth capacity. Second, only a few events are reported in normal cases, making control channels underloaded and wasting network resources. In this paper, we propose Escala to provide the elastic scaling of control channels at runtime. The key idea is to dynamically migrate event streams among control channels to regulate the loads of these channels. Escala offers two components, including an Escala monitor that detects scaling situations based on realtime network statistics, and an optimization framework that makes scaling decisions to eliminate overload and underload situations. We have implemented a prototype of Escala on Tofino-based switches. Extensive experiments show that Escala achieves timely elastic scaling while preserving high application-level accuracy.

Keyword:

Accuracy Atmospheric measurements Bandwidth control channel scaling Control systems Monitoring network event collection Network measurement Optimization Particle measurements programmable networks Runtime Servers Time measurement

Community:

  • [ 1 ] [Liu, Hongyan]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310007, Peoples R China
  • [ 2 ] [Chen, Xiang]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310007, Peoples R China
  • [ 3 ] [Kong, Dezhang]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310007, Peoples R China
  • [ 4 ] [Wu, Chunming]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310007, Peoples R China
  • [ 5 ] [Huang, Qun]Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
  • [ 6 ] [Zhang, Dong]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350116, Peoples R China
  • [ 7 ] [Liu, Xuan]Yangzhou Univ, Coll Informat Engn, Coll Artificial Intelligence, Yangzhou 225009, Peoples R China

Reprint 's Address:

  • [Chen, Xiang]Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310007, Peoples R China

Show more details

Version:

Source :

IEEE-ACM TRANSACTIONS ON NETWORKING

ISSN: 1063-6692

Year: 2024

Issue: 2

Volume: 33

Page: 777-792

3 . 0 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

30 Days PV: 1

Online/Total:30/10046711
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1