Name
Title | ||
|---|---|---|
Distributed topology construction algorithm to improve link quality and energy efficiency for wireless sensor networks. |
Abstract | ||
|---|---|---|
The evaluation of link quality plays a vital role in designing the upper level protocol in wireless sensor networks. The high rate of packet loss occurs when data is transmitting on the poor quality link, thus resulting in data retransmission and energy waste. Motivated with the aforementioned problem, we present the link weight model to address the problem of poor link quality and high energy consumption. This model regards the node's transmitting power as an adjustment factor. It fuses the link quality parameter and nodes' energy parameter to mathematically formulate the above problem for decreasing the interference and making the network energy balanced. Then exploiting the method of function derivation, we validate the analytical solution of the link weight. On the basis of this model, a distributed topology construction algorithm to improve link quality and energy efficiency is proposed. Finally several simulation experiments are conducted to evaluate the performance of this algorithm and validate its theoretical properties. Theoretical analyses and simulation results show that this algorithm can enhance the link steadiness, decrease the interference and prolong the network's lifetime. Display Omitted A model that represents bi-directional link communication quality is proposed.The link weight can lessen energy waste, and increase the network throughput.The algorithm relies on high quality of all the links in network. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.jnca.2016.04.017 | J. Network and Computer Applications |
Keywords | Field | DocType |
Wireless sensor networks,Link quality,Energy consumption,Link weight | Link adaptation,Efficient energy use,Retransmission,Computer science,Computer network,Packet loss,Algorithm,Interference (wave propagation),Fuse (electrical),Energy consumption,Wireless sensor network,Distributed computing | Journal |
Volume | Issue | ISSN |
72 | C | 1084-8045 |
Citations | PageRank | References |
3 | 0.38 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaochen Hao | 1 | 37 | 5.77 |
| Weijing Liu | 2 | 3 | 0.72 |
| ning yao | 3 | 5 | 2.81 |
| Dehua Geng | 4 | 4 | 0.77 |
| Xi-Da Li | 5 | 3 | 1.39 |