University of Sussex
Browse
07973018.pdf (761.91 kB)

Vertex entropy as a critical node measure in network monitoring

Download (761.91 kB)
journal contribution
posted on 2023-06-09, 06:57 authored by Philip Tee, George ParisisGeorge Parisis, Ian WakemanIan Wakeman
Understanding which node failures in a network have more impact is an important problem. Current understanding, motivated by the scale free models of network growth, places emphasis on the degree of the node. This is not a satisfactory measure; the number of connections a node has does not capture how redundantly it is connected into the whole network. Conversely, the structural entropy of a graph captures the resilience of a network well, but is expensive to compute, and, being a global measure, does not attribute any specific value to a given node. This lack of locality prevents the use of global measures as a way of identifying critical nodes. In this paper we introduce local vertex measures of entropy which do not suffer from such drawbacks. In our theoretical analysis we establish the possibility that our local vertex measures approximate global entropy, with the advantage of locality and ease of computation. We establish properties that vertex entropy must have in order to be useful for identifying critical nodes. We have access to a proprietary event, topology and incident dataset from a large commercial network. Using this dataset, we demonstrate a strong correlation between vertex entropy and incident generation over events.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

IEEE Transactions on Network and Service Management

ISSN

1932-4537

Publisher

Institute of Electrical and Electronics Engineers

Issue

3

Volume

14

Page range

646-660

Department affiliated with

  • Informatics Publications

Research groups affiliated with

  • Foundations of Software Systems Publications

Notes

(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2017-06-30

First Open Access (FOA) Date

2017-06-30

First Compliant Deposit (FCD) Date

2017-06-30

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC