Brisolara, Lisane, Ferreira, Paulo R. and Soares Indrusiak, Leandro orcid.org/0000-0002-9938-2920 (2016) Application modeling for performance evaluation on event-triggered wireless sensor networks. Design Automation for Embedded Systems. pp. 269-287. ISSN 1572-8080
Abstract
This paper presents an approach for event-triggered wireless sensor network (WSN) application modeling, aiming to evaluate the performance of WSN configurations with regards to metrics that are meaningful to specific application domains and respective end-users. It combines application, environment-generated workload and computing/communication infrastructure within a high-level modeling simulation framework, and includes modeling primitives to represent different kind of events based on different probabilities distributions. Such primitives help end-users to characterize their application workload to capture realistic scenarios. This characterization allows the performance evaluation of specific WSN configurations, including dynamic management techniques as load balancing. Extensive experimental work shows that the proposed approach is effective in verifying whether a given WSN configuration can fulfill non-functional application requirements, such as identifying the application behavior that can lead a WSN to a break point after which it cannot further maintain these requirements. Furthermore, through these experiments, we discuss the impact of different distribution probabilities to model temporal and spatial aspects of the workload on WSNs performance, considering the adoption of dynamic and decentralized load balancing approaches.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Science+Business Media New York 2016. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 13 Dec 2016 11:59 |
Last Modified: | 06 Feb 2025 00:07 |
Published Version: | https://doi.org/10.1007/s10617-016-9177-1 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1007/s10617-016-9177-1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109410 |