Name
Abstract | ||
|---|---|---|
In sparse wireless sensor networks, a UAV is used to collect the sensing data. Each sensor node has a limited transmission range and the UAV has to traverse the transmission range of all sensor nodes to collect data without exhausting energy of the UAV. To minimize the total energy consumption of the UAV on the flying and collecting data, it is essential to consider the tradeoff between path length and data collection time when planning path. In this paper, we show that the optimization problem can be regarded as the traveling salesman problem with neighborhood, which is known to be NP-hard. To address the problem, we decompose it into two subproblems, 1) weighted set cover problem; and 2) a combined optimization problem. Then we solve the first one by a greedy algorithm and the second by an improved shuffled frog-leaping algorithm. We also simulate the proposed algorithm to evaluate its performance. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/MSN.2018.00033 | 2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) |
Keywords | Field | DocType |
UAV,data collection,path planning,energy efficient | Motion planning,Sensor node,Set cover problem,Computer science,Real-time computing,Greedy algorithm,Travelling salesman problem,Wireless sensor network,Optimization problem,Distributed computing,Traverse | Conference |
ISBN | Citations | PageRank |
978-1-7281-0548-2 | 1 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baichuan Kong | 1 | 1 | 0.34 |
| Huang Hejiao | 2 | 307 | 37.23 |
| Xiaohua Jia | 3 | 4609 | 303.30 |