Name
Title | ||
|---|---|---|
A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks. |
Abstract | ||
|---|---|---|
We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network's topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/s18051434 | SENSORS |
Keywords | Field | DocType |
mobile sink,energy efficiency,fuzzy decision system,wireless sensor network,rendezvous point planning | Efficient energy use,Electronic engineering,Heuristics,Integer programming,Rendezvous,Path-constrained rendezvous,Engineering,Wireless sensor network,Energy consumption,Trajectory,Distributed computing | Journal |
Volume | Issue | Citations |
18 | 5.0 | 2 |
PageRank | References | Authors |
0.36 | 36 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmadreza Vajdi | 1 | 16 | 2.93 |
| Gongxuan Zhang | 2 | 94 | 19.89 |
| Junlong Zhou | 3 | 89 | 10.01 |
| Tongquan Wei | 4 | 250 | 22.62 |
| Yong-li Wang | 5 | 107 | 26.46 |
| Tianshu Wang | 6 | 13 | 2.67 |