Robustness Optimization of Wearable Networks
Date Issued
2015
Date
2015
Author(s)
Shih, Yuan-Yao
Abstract
Wearable networks have emerged recently to provide notification, news update, and health monitoring for normal people. In a wearable network, the human''s smartphone is deemed an appropriate gateway to help forward the sensing/update data to/from back-end servers. We observe that human mobility and postural changes can cause great impact on the network. Delivery failures from APs to the smartphone occur constantly due to human mobility, while temporary disconnection between sensors and the smartphone can happen frequently due to postural changes, causing a significant amount of data to be lost forever. In this thesis, to deal with the human mobility, we exploit the regularity in human mobility patterns to increase the data delivery ratio and mitigate the effects of packet loss caused by the human mobility. We propose a node deployment and tree construction framework; the effectiveness of network topologies constructed under the framework is demonstrated via comprehensive NS2 simulations based on two real-world scenarios. Then, to deal with the postural changes, we propose a scheme to parasitize the data in surrounding Wi-Fi networks whenever temporary disconnection occurs. To evaluate our scheme, we conduct a series of experiments with the prototype system in controlled and real-world environments. Finally, with the mobility issues appropriately addressed, we propose a rescue system which uses the Doppler effect to determine the direction of Wi-Fi signals emitted from disaster survivors'' mobile devices, to help the rescuers find those people in need more quickly. We implement the rescue system in a mobile application for Android smartphones and conduct extensive experiments.
Subjects
topology construction
data parasitizing
rescue missions
wearable networks
SDGs
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-104-D00922018-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):73b0575dbe98166b51979deba57904d0