Fault Tolerant Localization Based on K-means Clustering in Wireless Sensor Networks
| Autor: | K. V. Santhosh, Soumya J Bhat |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Majority rule
business.industry Computer science 010401 analytical chemistry Real-time computing k-means clustering 020206 networking & telecommunications Fault tolerance 02 engineering and technology 01 natural sciences 0104 chemical sciences Software Assisted GPS Node (computer science) 0202 electrical engineering electronic engineering information engineering Cluster analysis business Wireless sensor network |
| Zdroj: | 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). |
| DOI: | 10.1109/conecct50063.2020.9198415 |
| Popis: | Wireless Sensor Network (WSN) has been considered as an essential tool for many applications. Most of the applications of WSNs require the location of sensor nodes to be known. But, because of high power consumption and cost, it is not suitable to attach a GPS receiver with every node. For estimating the location of sensor nodes, localization algorithms make use of few location-aware nodes as reference nodes. But, sometimes, these reference nodes can turn faulty. They may estimate their locations wrongly due to software or hardware malfunctions. This affects the localization of the entire network. To overcome this problem, we have reported a fault tolerant localization algorithm called clustering based DV-Hop. This algorithm filters out faulty nodes using K-means clustering and majority voting methods. The performance of the algorithm is then compared with other localization algorithms. The reported algorithm shows better localization accuracies and more stable performance under faulty conditions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|