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Completion time minimization for distributed feature extraction in a visual sensor network testbed
KTH, School of Electrical Engineering (EES), Communication Networks.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Real-time detection and extraction of visual features in wireless sensor

networks is a challenging task due to its computational complexity and

the limited processing power of the nodes. A promising approach is to

distribute the workload to other nodes of the network by delegating the

processing of different regions of the image to different nodes. In this

work a solution to optimally schedule the loads assigned to each node is

implemented on a real visual sensor network testbed. To minimize the

time required to process an image, the size of the subareas assigned to

the cooperators are calculated by solving a linear programming problem

taking into account the transmission and processing speed of the nodes

and the spatial distribution of the visual features. In order to minimize

the global workload, an optimal detection threshold is predicted such that

only the most significant features are extracted. The solution is implemented

on a visual sensor network testbed consisting of BeagleBone Black

computers capable of communicating over IEEE 802.11. The capabilities

of the testbed are also extended by adapting a reliable transmission protocol

based on UDP capable of multicast transmission. The performance

of the implemented algorithms is evaluated on the testbed.

Place, publisher, year, edition, pages
2014. , 63 p.
EES Examensarbete / Master Thesis, XR-EE-LCN 2014:010
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-156883OAI: diva2:768333
Available from: 2014-12-08 Created: 2014-12-03 Last updated: 2014-12-08Bibliographically approved

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