Name
Title | ||
|---|---|---|
Towards Energy Efficient Duty-Cycled Networks: Analysis, Implications and Improvement |
Abstract | ||
|---|---|---|
Duty cycling mode is widely adopted in wireless sensor networks to save energy. Existing duty-cycling protocols cannot well adapt to different data rates and dynamics, resulting in a high energy consumption in real networks. Improving those protocols may require global information or heavy computation and thus may not be practical, leading to many empirical parameters in real protocols. To fill the gap between the application requirement and protocol performance, in this paper, we analyze the energy consumption for duty cycled sensor networks with different data rates. Our analysis shows that existing protocols cannot lead to an efficient energy consumption in various scenarios. Based on the analysis, we design a light-weight adaptive duty-cycling protocol (LAD), which reduces the energy consumption under different data rates and protocol dynamics. LAD can adaptively adjust the protocol parameters according to network conditions such as data rate and achieve an optimal energy efficiency. To make LAD practical in real network, we further precalculate optimal parameters offline and store them on sensor nodes, which significantly reduces the computation time.We theoretically validate the performance improvement of the protocol. We implement the protocol in TinyOS and extensively evaluate it on 40 TelosB nodes. The evaluation results show the energy consumption can be reduced by 28.2%∼40.1% compared with state-of-the-art protocols. Results based on data from a 1200-node operational network further show the effectiveness and scalability of the design. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TC.2015.2417558 | Computers, IEEE Transactions |
Keywords | Field | DocType |
sensors,wireless sensor networks | Key distribution in wireless sensor networks,Efficient energy use,Computer science,Real-time computing,Data rate,Energy consumption,Wireless sensor network,Computation,Scalability,Performance improvement | Journal |
Volume | Issue | ISSN |
PP | 99 | 0018-9340 |
Citations | PageRank | References |
4 | 0.44 | 23 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiliang Wang | 1 | 564 | 43.33 |
| Zhichao Cao | 2 | 172 | 23.04 |
| XuFei Mao | 3 | 858 | 45.54 |
| Xiang-Yang Li | 4 | 6855 | 435.18 |
| Yunhao Liu | 5 | 8810 | 486.66 |