Healing of large‐scale failures in WSN by the effectual placement of relay nodes
| Autor: | Krishnan Murugan, Gopinathan Rajeswari |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Minimisation (psychology)
Degree (graph theory) business.industry Computer science Node (networking) 020206 networking & telecommunications 020302 automobile design & engineering 02 engineering and technology Disjoint sets Average path length Computer Science Applications Network simulation law.invention 0203 mechanical engineering Relay law 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Wireless sensor network Computer network |
| Zdroj: | IET Communications. 14:3030-3038 |
| ISSN: | 1751-8636 1751-8628 |
| DOI: | 10.1049/iet-com.2020.0320 |
| Popis: | The lightening growth in Internet of Things (IoT), forced the deployment of various types of applications. Due to the likelihood of sensor failures, the applications of IoT cannot be benefited. These node failures can transform the fully-connected network into multiple disjoint sub-networks, named network partitioning problem where the nodes fail to perform intended services. The federation of these isolated network segments is essential. In this study, a distributed approach FRTP (Failure Recovery using Relay Nodes at Torricelli points ( T p )) is proposed, where the restoration of the disconnected network is initiated using the relay nodes (RNs). The performance of FRTP is evaluated using network simulator tool NS-2 and the experimental results show that it achieves better performance than the existing approaches. The main goal of the proposed approach is to minimise the number of HRNs (Healing Relay Nodes), APL (Average path length), recovery time of the network and to maximise the average node degree. The average improvement in minimisation of number of HRN, APL, and recovery time of the network for radio range of 100 m are 21.57, 13.23, and 9.96%, respectively, and the maximisation of average node degree is 9.83%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text