Τίτλος:
Context Monitoring Optimization in Autonomic Networks
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
The recent advances in network management systems suggest the adoption of autonomic mechanisms in order to minimize the need for human intervention while handling complex heterogeneous networks. Data acquisition performed by monitoring processes is an essential part of autonomic mechanisms. The rate of sampling is a crucial factor since it is related to (1) the successful/unsuccessful detection of events, (2) the processing power needed to perform the sampling and (3) the energy that a node consumes during such actions. In order to address these issues we designed a simple and efficient mechanism that dynamically adapts the sampling rate of the context monitoring procedure. The merits of the mechanism are quantified by means of an analytical model as well as through extensive simulations that validated the theoretic outcomes. Finally, we experimentally assessed the effectiveness and efficiency of our approach through two real-world experiments. Overall results showcase that our mechanism achieves high detection rates while in parallel minimizes significantly the number of monitoring loops thus, emerges as a viable approach for context monitoring optimization in autonomic networks. © 2014, Springer Science+Business Media New York.
Συγγραφείς:
Magdalinos, P.
Kaloxylos, A.
Alonistioti, N.
Περιοδικό:
Wireless Personal Communications
Εκδότης:
Kluwer Academic Publishers
Λέξεις-κλειδιά:
Data acquisition; Heterogeneous networks, Autonomic mechanisms; Autonomic networking; Context- awareness; Effectiveness and efficiencies; Extensive simulations; In-network management; Monitoring optimizations; Real world experiment, Monitoring
DOI:
10.1007/s11277-014-2128-x
