Investigating the Resilience of Unstructured Supernode Networks

Author

Amoretti, Michele ; Ferrari, Giorgio

Author_Institution

Centro Interdipt. SITEIA.Parma, Univ. degli Studi di Parma, Parma, Italy

Volume

17

Issue

6

fYear

2013

fDate

Jun-13

Firstpage

1272

Lastpage

1275

Abstract

In this letter, we present a novel analytical framework to analyze the resilience of Unstructured Supernode Networks (USNs), where a "leaf" node can be promoted, after a fixed time interval, to the role of "supernode," with non-preferential attachment to a given number of existing supernodes. In particular, relying on an Absorbing Markov Chain (AMC)-based model of a supernode behavior, we derive an efficient approximation of the node degree distribution of an USN. This model also allows to estimate a supernode\´s probability of isolation. The proposed analytical framework is validated by simulation results.

Keywords

Markov processes; approximation theory; peer-to-peer computing; probability; AMC; USN; absorbing Markov chain based model; approximation theory; fixed time interval; node degree distribution; nonpreferential attachment; peer-to-peer network; resilience investigation; supernode isolation probability estimation; unstructured supernode network; Analytical models; Exponential distribution; Markov processes; Peer-to-peer computing; Resilience; Simulation; Absorbing Markov Chain (AMC); Peer-to-peer; network resilience;

fLanguage

English

Journal_Title

Communications Letters, IEEE

Publisher

ieee

ISSN

1089-7798

Type

jour

DOI

10.1109/LCOMM.2013.043013.130305

Filename

6515207