Name
Title | ||
|---|---|---|
On the Topology Effects in Wireless Sensor Networks Based Prognostics and Health Management |
Abstract | ||
|---|---|---|
In this work, we consider the usage of wireless sensor networks (WSN) to monitor an area of interest, in order to diagnose on real time its state. Each sensor node forwards information about relevant features towards the sink where the data is processed. Nevertheless, energy conservation is a key issue in the design of such networks and once a sensor exhausts its resources, it will be dropped from the network. This will lead to broken links and data loss. It is therefore important to keep the network running for as long as possible by preserving the energy held by the nodes. Indeed, saving the quality of service (QoS) of a wireless sensor network for a long period is very important in order to ensure accurate data. Then, the area diagnosing will be more accurate. From another side, packet transmission is the phase that consumes the highest amount of energy comparing to other activities in the network. Therefore, we can see that the network topology has an important impact on energy efficiency, and thus on data and diagnosis accuracies. In this paper, we study and compare four network topologies: distributed, hierarchical, centralized, and decentralized topology and show their impact on the resulting estimation of diagnostics. We have used six diagnostic algorithms, to evaluate both prognostic and health management with the variation of type of topology in WSN. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CSE-EUC-DCABES.2016.205 | 2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES) |
Keywords | DocType | Volume |
wireless sensor networks,health management,sensor node,energy conservation,sensor exhausts,quality of service,QoS,packet transmission,network topology,energy efficiency,diagnosis accuracy,distributed topology,hierarchical topology,decentralized topology,diagnostics estimation | Journal | abs/1708.05965 |
ISBN | Citations | PageRank |
978-1-5090-3594-6 | 0 | 0.34 |
References | Authors | |
9 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmad Farhat | 1 | 0 | 0.34 |
| Abdallah Makhoul | 2 | 299 | 36.48 |
| Christophe Guyeux | 3 | 332 | 61.61 |
| Rami Tawil | 4 | 36 | 4.36 |
| Ali Jaber | 5 | 36 | 6.21 |
| Abbas Hijazi | 6 | 12 | 3.31 |