Topology Change Algorithms based on Fluid Flow and Flock Dispersion for Energy-Harvesting Mobile Sensor Networks

2013 ◽  
Vol 50 (12) ◽  
pp. 98-106
Author(s):  
Wonho So
Keyword(s):  
Fluid Flow ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Mobile Sensor Networks ◽  
Mobile Sensor ◽  
Topology Change

scholarly journals Fair Scheduling for Data Collection in Mobile Sensor Networks with Energy Harvesting

2019 ◽  
Vol 18 (6) ◽  
pp. 1274-1287 ◽  
Author(s):  
Kai Li ◽  
Chau Yuen ◽  
Branislav Kusy ◽  
Raja Jurdak ◽  
Aleksandar Ignjatovic ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Energy Harvesting ◽  
Data Collection ◽  
Mobile Sensor Networks ◽  
Mobile Sensor ◽  
Fair Scheduling

Relative Distance-Aware Data Delivery Scheme for Delay Tolerant Mobile Sensor Networks

2010 ◽  
Vol 21 (3) ◽  
pp. 490-504 ◽  
Author(s):  
Fu-Long XU ◽  
Ming LIU ◽  
Hai-Gang GONG ◽  
Gui-Hai CHEN ◽  
Jian-Ping LI ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Relative Distance ◽  
Data Delivery ◽  
Mobile Sensor ◽  
Delay Tolerant

Group Mobility Adaptive Event Delivery Scheme for Delay Tolerant Mobile Sensor Networks

2012 ◽  
Vol 23 (3) ◽  
pp. 629-647 ◽  
Author(s):  
Lei WU ◽  
Xiao-Min WANG ◽  
Ming LIU ◽  
Gui-Hai CHEN ◽  
Hai-Gang GONG
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Mobile Sensor ◽  
Group Mobility ◽  
Delay Tolerant

Tips on Stochastic Optimal Feedback Control and Bayesian Spatiotemporal Models: Applications to Robotics

2014 ◽  
Vol 137 (3) ◽  
Author(s):  
Jongeun Choi ◽  
Dejan Milutinović
Keyword(s):  
Sensor Networks ◽  
Feedback Control ◽  
Control Theory ◽  
Mobile Sensor Networks ◽  
Optimal Feedback Control ◽  
Mobile Sensor ◽  
Optimal Feedback ◽  
Spatiotemporal Models ◽  
Feedback Control Theory

This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.

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