Filters








61,165 Hits in 4.4 sec

Robust Self-stabilizing Clustering Algorithm [chapter]

Colette Johnen, Le Huy Nguyen
2006 Lecture Notes in Computer Science  
Due to this property, self-stabilizing algorithms tolerate transient faults. In this paper we present a robust self-stabilizing clustering algorithm for ad hoc network.  ...  A self-stabilizing algorithm, regardless of the initial system state, converges in finite time to a set of states that satisfy a legitimacy predicate without external intervention.  ...  Several self-stabilizing algorithms for clusters formation and clusterheads selection have been proposed [5, 20, 17] . These algorithms are not robust.  ... 
doi:10.1007/11945529_29 fatcat:2cpkb6l5pfcw3lit6vcfbdmwhu

Robust self-stabilizing weight-based clustering algorithm

Colette Johnen, Le Huy Nguyen
2009 Theoretical Computer Science  
In this paper, we present a robust self-stabilizing weight-based clustering algorithm for ad hoc networks.  ...  A self-stabilizing algorithm, regardless of the initial system configuration, converges to legitimate configurations without external intervention.  ...  A self-stabilizing algorithm for cluster formation is presented in [23] .  ... 
doi:10.1016/j.tcs.2008.10.009 fatcat:amyspnbitzfmjmjdifaukyhvne

Autonomic Request Management Algorithms for Geographically Distributed Internet-Based Systems

Mauro Andreolini, Sara Casolari, Michele Colajanni
2008 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems  
Experimental evaluation shows that our autonomic-enhanced algorithms can guarantee robust performance in a variety of settings and reduce standard deviations of the response times with respect to existing  ...  request management algorithms.  ...  It is self-adaptable and guarantees best stability especially when it is enriched by a probabilistic approach to decide about redirection.  ... 
doi:10.1109/saso.2008.32 dblp:conf/saso/AndreoliniCC08 fatcat:7hu7fc7mcnecjm4buqjaw7lrea

Network Scaffolding for Efficient Stabilization of the Chord Overlay Network [article]

Andrew Berns
2021 arXiv   pre-print
For non-trivial topologies that have desirable properties like low diameter and robust routing in the face of node or link failures, self-stabilizing algorithms to date have had at least linear running  ...  Designing efficient self-stabilizing algorithms for many topologies, however, is not an easy task.  ...  The Problem Our focus is on building robust self-stabilizing overlay networks efficiently.  ... 
arXiv:2109.14126v1 fatcat:oswlvqqflbguja5eeqi7jpz5lu

Energy-Aware Self-Stabilizing Distributed Clustering Protocol for Ad Hoc Networks: the case of WSNs

2013 KSII Transactions on Internet and Information Systems  
In this paper, we present an Energy-Aware Self-Stabilizing Distributed Clustering protocol based on message-passing model for Ad Hoc networks. The latter does not require any initialization.  ...  number in the clusters.  ...  They have proposed a robust self-stabilizing weight-based clustering algorithm.  ... 
doi:10.3837/tiis.2013.11.002 fatcat:kszjbtdytzddbae4ob7ifijkam

A robustness metric for biological data clustering algorithms

Yuping Lu, Charles A. Phillips, Michael A. Langston
2019 BMC Bioinformatics  
Other techniques exhibited mixed robustness, with no clear distinction between them. Robustness provides a simple and intuitive measure of the stability and predictability of a clustering algorithm.  ...  Comparisons between clustering algorithms tend to focus on cluster quality.  ...  The metric we introduce, which we term "robustness", provides a relatively simple measure of a clustering algorithm's stability over a range of these settings.  ... 
doi:10.1186/s12859-019-3089-6 pmid:31874625 pmcid:PMC6929270 fatcat:kvxfzv7d35fdxispn5ddx5smgq

Page 578 of Human Biology Vol. 83, Issue 5 [page]

2011 Human Biology  
In addition to the increased stability of the results, consensus clustering can provide a range of metrics to help inform the optimum number of clusters as well as the robustness of the resulting cluster  ...  The method is designed to increase the stability of the final cluster outcomes by taking the consensus of multiple runs of a single cluster algorithm.  ... 

Self-Stabilizing Computation and Preservation of Knowledge of Neighbor Clusters

Colette Johnen, Fouzi Mekhaldi
2011 2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems  
The area of self-stabilization in large scale networks has been received increasing attention among researchers, since self-stabilization provides a foundation for self-properties, including self-healing  ...  Second, we propose a self-stabilizing protocol computing and preserving the knowledge of neighbor clusters, called CNK.  ...  There are also robust self-stabilizing clustering algorithms [16] , [13] , and selfstabilizing with safe convergence [18] .  ... 
doi:10.1109/saso.2011.15 dblp:conf/saso/JohnenM11 fatcat:kguyohn4bfeyvjmrzf363nsixy

Symmetry-independent stability analysis of synchronization patterns [article]

Yuanzhao Zhang, Adilson E. Motter
2020 arXiv   pre-print
Here, we establish a generalization of the MSF formalism that can characterize the stability of any cluster synchronization pattern, even when the oscillators and/or their interactions are nonidentical  ...  This leads to an algorithm that is error-tolerant and orders of magnitude faster than existing symmetry-based algorithms.  ...  This results in an algorithm that is faster, simpler, and more robust than the state-of-the-art algorithm based on irreducible representations of network symmetry.  ... 
arXiv:2003.05461v1 fatcat:w6acsvn7sncqtg5ajabwletnc4

Symmetry-Independent Stability Analysis of Synchronization Patterns

Yuanzhao Zhang, Adilson E. Motter
2020 SIAM Review  
This leads to an algorithm that is error-tolerant and orders of magnitude faster than existing symmetry-based algorithms.  ...  Here, we establish a generalization of the MSF formalism that can characterize the stability of any cluster synchronization pattern, even when the oscillators and/or their interaction functions are nonidentical  ...  This results in an algorithm that is faster, simpler, and more robust than Downloaded 01/11/21 to 207.241.229.224.  ... 
doi:10.1137/19m127358x fatcat:b244hpb7pjcxvdaqsqjbjs6vaq

Combined Mapping of Multiple clUsteriNg ALgorithms (COMMUNAL): A Robust Method for Selection of Cluster Number, K

Timothy E. Sweeney, Albert C. Chen, Olivier Gevaert
2015 Scientific Reports  
map of cluster stability that can help determine the optimal number of clusters in a data set, a technique we call COmbined Mapping of Multiple clUsteriNg ALgorithms (COMMUNAL).  ...  behavior and stability in all tested cases.  ...  k-means, self-organizing maps 9 , partitioning around medioids, clustering for large applications 10 , and the self-organizing tree algorithm 11 ).  ... 
doi:10.1038/srep16971 pmid:26581809 pmcid:PMC4652212 fatcat:y2cbrmh25zc3xjiayk4bys7qum

Introduction: Data Communication and Topology Algorithms for Sensor Networks

Stephan Olariu, David Simplot-Ryl, Ivan Stojmenovic
2005 International Journal of Distributed Sensor Networks  
They cover specific problems such as time division for reduced collision, fault tolerant clustering, self-stabilizing graph optimization algorithms, key pre-distribution for secure communication, and distributed  ...  Goddard, Hedetniemi, Jacobs, and Srimani propose self-stabilizing algorithms for three graph optimization problems: a minimal total dominating set (where every node must be adjacent to a node in the set  ... 
doi:10.1080/15501320500433754 fatcat:tvkv2spigfg2rkl3kai76hocoy

Progeny Clustering: A Method to Identify Biological Phenotypes

Chenyue W. Hu, Steven M. Kornblau, John H. Slater, Amina A. Qutub
2015 Scientific Reports  
Self-Organizing Maps 13 , Affinity Propogation 14 ), most clustering algorithms (including the popular clustering methods k-means 15 and hierarchical clustering 16 ) require input from users to specify  ...  The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome  ...  Instead of directly measuring cluster compactness and separation, stability-based methods evaluate how robust the clustering is against the randomness in sampling.  ... 
doi:10.1038/srep12894 pmid:26267476 pmcid:PMC4533525 fatcat:temtn7slb5dzbjoxufckk4cagm

On the Performances of the Routing Protocols in MANET: Classical Versus Self-organized Approaches [chapter]

Fabrice Theoleyre, Fabrice Valois
2006 Lecture Notes in Computer Science  
VSR is based on a self-organized structure with an important stability and persistence.  ...  We oppose VSR as a self-organized protocol to the classical one: reactive (AODV), proactive (OLSR) and clustered (CBRP).  ...  VSR is based on self-organization paradigms and benefits of the stability and robustness properties of the virtual structure.  ... 
doi:10.1007/11753810_68 fatcat:4t5vncpl4bfm7imsrah6zdu66a

DAOC: Stable Clustering of Large Networks [article]

Artem Lutov, Mourad Khayati, Philippe Cudré-Mauroux
2019 arXiv   pre-print
Data diversity calls for clustering algorithms to be accurate while providing stable (i.e., deterministic and robust) results on arbitrary input networks.  ...  In addition, it leverages a novel consensus approach, Mutual Maximal Gain, to ensure robustness and further improve the stability of the results while still being capable of identifying micro-scale clusters  ...  Stability Evaluation We evaluate stability in terms of both robustness and determinism for the consensus (ensemble) and deterministic clustering algorithms listed in Table II .  ... 
arXiv:1909.08786v2 fatcat:mswptiwr4nh53khdvt4et2ag4m
« Previous Showing results 1 — 15 out of 61,165 results