A Grid-Based Reliable Routing (GBRR) protocol for wireless sensor networks
Since the sensors have the characteristics of self-organizing and low cost and the wireless sensor network develops rapidly, more reliable routing algorithms are required to perform better forwarding. In wireless sensor network, due to the limited power and the non-equivalence of the sensor nodes, i...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/82975/1/FSKTM%202019%2029%20IR.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Since the sensors have the characteristics of self-organizing and low cost and the wireless sensor network develops rapidly, more reliable routing algorithms are required to perform better forwarding. In wireless sensor network, due to the limited power and the non-equivalence of the sensor nodes, it is necessary to reduce energy consumption reasonably to prolong the network lifetime. In the traditional protocols, energy model is adopted by LEACH with uniform distribution of sensor nodes and without the consideration of residual energy, which leads to the large number of packets dropped and instable network environment. When encountering the obstacles and voids, the routing with perimeter and greedy algorithms are unable to proceed. In order to balance and minimize the energy consumption, a Grid-Based Reliable Routing (GBRR) protocol is presented. In this research, collaborated with clustering and grid-based routing features, the proposed protocol uses a combination of clustering protocols and geographical protocols with greedy algorithm to accomplish the scalability and adaptability of the randomly deployed sensor networks in a dense and large-scale network. By adopting right hand rule strategy, the packets walk around the perimeter and voids are avoided. Simulation was adopted using MATLAB. The simulation results show that the GBRR efficiently identifies the redundant nodes and reroutes them avoiding obstacles and voids while improving network lifetime and energy consumption. |
|---|