eprintid: 10060070
rev_number: 22
eprint_status: archive
userid: 608
dir: disk0/10/06/00/70
datestamp: 2018-10-30 12:37:56
lastmod: 2021-09-25 23:13:07
status_changed: 2019-02-27 16:29:53
type: article
metadata_visibility: show
creators_name: Tangari, G
creators_name: Tuncer, D
creators_name: Charalambides, M
creators_name: Qi, Y
creators_name: Pavlou, G
title: Self-Adaptive Decentralized Monitoring in Software-Defined Networks
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F46
keywords: Monitoring, Switches, Hardware, Synchronization, Resource management, Task analysis,Frequency measurement, Network monitoring, Software-Defined Networks, Self-adaptation.
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: The Software-Defined Networking (SDN) paradigm can allow network management solutions to automatically and frequently reconfigure network resources. When developing SDNbased management architectures, it is of paramount importance to design a monitoring system that can provide timely and consistent updates to heterogeneous management applications. To support such applications operating with low latency requirements, the monitoring system should scale with increasing network size and provide precise network views with minimum overhead on the available resources. In this paper we present a novel, self-adaptive, decentralized framework for resource monitoring in SDN. Our framework enables accurate statistics to be collected with limited burden on the network resources. This is realized through a self-tuning, adaptive monitoring mechanism that automatically adjusts its settings based on the traffic dynamics. We evaluate our proposal based on a realistic use case scenario, where a content distribution service and an on-demand gaming platform are deployed within an ISP network. The results show that reduced monitoring latencies are obtained with the proposed framework, thus enabling shorter reconfiguration control loops. In addition, the proposed adaptive monitoring method achieves significant gain in terms of monitoring overhead, while preserving the performance of the services considered.
date: 2018-12
date_type: published
official_url: https://doi.org/10.1109/TNSM.2018.2874813
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1597401
doi: 10.1109/TNSM.2018.2874813
lyricists_name: Charalambides, Marinos
lyricists_name: Pavlou, George
lyricists_name: Tangari, Gioacchino
lyricists_id: MCHAR90
lyricists_id: GPAVL62
lyricists_id: GTANG64
actors_name: Pavlou, George
actors_id: GPAVL62
actors_role: owner
full_text_status: public
publication: IEEE Transactions on Network and Service Management
volume: 15
number: 4
pagerange: 1277-1291
issn: 1932-4537
citation:        Tangari, G;    Tuncer, D;    Charalambides, M;    Qi, Y;    Pavlou, G;      (2018)    Self-Adaptive Decentralized Monitoring in Software-Defined Networks.                   IEEE Transactions on Network and Service Management , 15  (4)   pp. 1277-1291.    10.1109/TNSM.2018.2874813 <https://doi.org/10.1109/TNSM.2018.2874813>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10060070/1/Tangari-18-TNSM.pdf