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A survey and performance evaluation of decentralized aggregation schemes for autonomic management
Author(s) -
Makhloufi Rafik,
Doyen Guillaume,
Bonnet Grégory,
Gaïti Dominique
Publication year - 2014
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.1875
Subject(s) - computer science , context (archaeology) , scheme (mathematics) , service (business) , data aggregator , taxonomy (biology) , network management , process management , risk analysis (engineering) , computer network , wireless sensor network , mathematical analysis , paleontology , botany , business , economy , mathematics , economics , biology , medicine
SUMMARY Over the last few years, autonomic network and service management has emerged as a serious alternative to traditional management approaches. In these systems, distributed entities, called autonomic managers, perform monitoring and control operations in an autonomous and decentralized way. The monitoring consists of providing indicators on the state of the system. Several monitoring solutions have been proposed to enable autonomic managers to obtain a partial or complete knowledge of an indicator through aggregation processes. Such a profusion of solutions raises important questions regarding the choice of an aggregation scheme in a particular operational context and for a particular management information because each class of solution presents different benefits and weaknesses. That is why, in this paper, we present the result of our study of decentralized aggregation schemes for autonomic network and service monitoring. The contribution is twofold: (i) a survey of decentralized aggregation schemes based on a refined taxonomy; and (ii) the results of an evaluation campaign we performed to compare typical aggregation schemes. These results highlight the context, in terms of the managed network behaviour as well as information dynamics, in which each aggregation scheme outperforms the others, thus helping autonomic management system designers in choosing the best scheme for their management purpose. Copyright © 2014 John Wiley & Sons, Ltd