Name
Abstract | ||
|---|---|---|
The rechargeable sensor network is promising for various applications. However, improving network performance is challenging, because the energy depletion of the sensor nodes will result in abnormal death of the nodes. In this paper, we propose a hybrid framework to model the abnormal death of the sensor nodes. Based on the Markov fluid queue theory, the model includes three parts, namely utilizing a Markov process to simulate the charging behavior, a queuing model to trace the working mechanism of rechargeable sensor nodes, and a continuous fluid process to indicate the energy level of sensor nodes. The numerical results show that our model can effectively predict the probability of abnormal death and stationary energy consumption of the sensor nodes. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISPA/IUCC.2017.00122 | 2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017) |
Keywords | Field | DocType |
Wireless rechargeable sensor network, Markov fluid queue, abnormal death, stationary energy consumption | Markov process,Computer science,Markov chain,Fluid queue,Real-time computing,Queueing theory,Human–computer interaction,Energy consumption,Wireless sensor network,Network performance | Conference |
ISSN | Citations | PageRank |
2158-9178 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ping Zhong | 1 | 28 | 4.89 |
| Yiwen Zhang | 2 | 28 | 5.81 |
| Jianliang Gao | 3 | 106 | 20.98 |
| Yiming Zhang | 4 | 143 | 37.82 |
| Jize Yan | 5 | 2 | 1.10 |