TY - GEN

T1 - Probing based topology inference for large scale community networks

AU - Zhanikeev, Marat

AU - Tanaka, Yoshiaki

AU - Ogishi, Tomohiko

N1 - Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2008

Y1 - 2008

N2 - Traditional research in on-demand topological solutions is gathered around the two main clusters, - wireless ad-hoc networks and fixed overlay networks. Both are very different in nature, but they both deal with the same problem which is to create a topology out of an arbitrary set of nodes. This paper considers the case of an arbitrary set of mixed-technology nodes which are to be joined in a topology based on end-to-end delay measurements among nodes. The core of the proposal is topology inference based on triangular inequality of end-to-end delay which is finalized in form of an algorithm that allows for efficient detection of a logical topology of a network with no initial topology. The algorithm is scalable and could be a practical solution for many scenarios involving community services created on-demand and intended for a short lifespan.

AB - Traditional research in on-demand topological solutions is gathered around the two main clusters, - wireless ad-hoc networks and fixed overlay networks. Both are very different in nature, but they both deal with the same problem which is to create a topology out of an arbitrary set of nodes. This paper considers the case of an arbitrary set of mixed-technology nodes which are to be joined in a topology based on end-to-end delay measurements among nodes. The core of the proposal is topology inference based on triangular inequality of end-to-end delay which is finalized in form of an algorithm that allows for efficient detection of a logical topology of a network with no initial topology. The algorithm is scalable and could be a practical solution for many scenarios involving community services created on-demand and intended for a short lifespan.

UR - http://www.scopus.com/inward/record.url?scp=57049173342&partnerID=8YFLogxK

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U2 - 10.1007/978-3-540-88623-5_10

DO - 10.1007/978-3-540-88623-5_10

M3 - Conference contribution

AN - SCOPUS:57049173342

SN - 3540886222

SN - 9783540886228

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 92

EP - 101

BT - Challenges for Next Generation Network Operations and Service Management - 11th Asia-Pacific Network Operations and Management Symposium, APNOMS 2008, Proceedings

PB - Springer Verlag

T2 - 11th Asia-Pacific Network Operations and Management Symposium, APNOMS 2008

Y2 - 22 October 2008 through 24 October 2008

ER -