An improved DV-Hop localization algorithm based on evolutionary algorithms
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Localization is one of the most important issues in wireless sensor networks and designing accurate localization algorithms is a common challenge in recent researches. Among all localization algorithms, DV-Hop attracts more attention due to its simplicity; so, we use it as a basis for our localization algorithm in order to improve accuracy. The various evolutionary algorithms such as Genetic, Shuffled Frog Leaping and Particle Swarm Optimization are employed in different phases of the main DV-Hop localization algorithm. Simulation results prove that our proposed method decreases the localization error efficiently without additional hardware.
Details
| Original language | English |
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| Pages (from-to) | 639-647 |
| Number of pages | 9 |
| Journal | Telecommunication Systems |
| Volume | 64 |
| Issue number | 4 |
| Publication status | Published - 1 Apr 2017 |
| Peer-reviewed | Yes |
| Externally published | Yes |
External IDs
| Scopus | 85055711318 |
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Keywords
Research priority areas of TU Dresden
Keywords
- DV-Hop, Genetic algorithm, Localization, Particle swarm optimization algorithm, Shuffled frog leaping algorithm, Wireless sensor networks