Advanced Faults Patterns for WSN Dependability Benchmarking - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2010

Advanced Faults Patterns for WSN Dependability Benchmarking

Ali Asim
  • Fonction : Auteur
Sébastien Tixeuil

Résumé

Wireless sensor networks are typically deployed in uncon- trolled environments that have high impact on the individ- ual nodes' reliability and ability to sustain effective service for a particular application, not to mention the failure probability that increases with the size of the network itself. The high cost induced by the deployment of WSN at large scale largely prevents the use of hardware and software based fault injection, leaving simulation-based tool the only remaining option. To date, most of simulation tools for WSN do not provide extensive modules for dependability benchmarking, which leaves the protocol designers to use either external fault-injection tools of modifying the code of the application to ``simulate'' faults. Those two factors makes using realistic fault patterns difficult and might impact the real-time behavior of the applications. In this paper, we propose a new model for describing advanced fault patterns, that subsumes previously used models for characterizing faulty behaviors. We implement the model in the WSNet simulator as an intermediate layer that is distinct from any layer in the protocol stack. Our modified WSNet is then used for extensive dependability benchmarking using typical WSN application, matching both real-life fault patterns and specific attacks that evolve over time.
Fichier non déposé

Dates et versions

hal-01290826 , version 1 (18-03-2016)

Identifiants

Citer

Ali Asim, Sébastien Tixeuil. Advanced Faults Patterns for WSN Dependability Benchmarking. The 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems, MSWiM 2010, Oct 2010, Bodrum, Turkey. pp.39-48, ⟨10.1145/1868521.1868530⟩. ⟨hal-01290826⟩
55 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More