.png){kind=icon}
Return
Flocking based distributed self-deployment algorithms in mobile sensor networks
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2011.11.013.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we address a novel deployment problem in isotropic mobile sensor networks. Sensors are to be relocated uniformly in a region of interest (ROI) centered at a target of interest (TOI) which could be stationary or mobile. With the assumption that relative direction of a sensor to the TOI can be recognized or inferred by devices equipped in the sensor, distributed control algorithms based on first-order and second-order dynamic models are proposed for both stationary and mobile TOI situations. The Lyapunov stabilities and coverage guarantee are provided. To further improve the deployment such as coverage holes inside the network and uniformity of the deployment, four assisted rules are also proposed. Then algorithms proposed for the situation of a stationary TOI are extended to anisotropic sensor networks. Simulations demonstrate the effective performances of the proposed algorithms. (C) 2011 Elsevier Inc. All rights reserved.
Keywords:
Sensor deployment
Mobile sensor network
Consensus
Flocking
Triangle tessellation
Journal
IF:
4
Papers:
3.8K
Citations:
4.8K
Organization
Cited Papers
ShareSaveShareSaveShareSaveInhibition of myeloperoxidase by N-acetyl lysyltyrosylcysteine amide reduces experimental autoimmune encephalomyelitis-induced injury and promotes oligodendrocyte regeneration and neurogenesis in a murine model of progressive multiple sclerosis.png)
NeuroReport
OAAI
NeuroReportIF0
OAAIShareSave
View more