Wireless visual sensor network resource allocation using cross-layer optimization

2009 ◽  
Author(s):  
Elizabeth S. Bentley ◽  
John D. Matyjas ◽  
Michael J. Medley ◽  
Lisimachos P. Kondi
Keyword(s):  
Resource Allocation ◽  
Sensor Network ◽  
Cross Layer ◽  
Visual Sensor ◽  
Network Resource ◽  
Visual Sensor Network ◽  
Cross Layer Optimization ◽  
Network Resource Allocation

Spread Spectrum Visual Sensor Network Resource Management Using an End-to-End Cross-Layer Design

2011 ◽  
Vol 13 (1) ◽  
pp. 125-131 ◽  
Author(s):  
Elizabeth S. Bentley ◽  
Lisimachos P. Kondi ◽  
John D. Matyjas ◽  
Michael J. Medley ◽  
Bruce W. Suter
Keyword(s):  
Resource Management ◽  
Sensor Network ◽  
Spread Spectrum ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Visual Sensor ◽  
Network Resource ◽  
Visual Sensor Network ◽  
Network Resource Management ◽  
End To End

Motion–Related Resource Allocation in Dynamic Wireless Visual Sensor Network Environments

2014 ◽  
Vol 23 (1) ◽  
pp. 56-68 ◽  
Author(s):  
Angeliki V. Katsenou ◽  
Lisimachos P. Kondi ◽  
Konstantinos E. Parsopoulos
Keyword(s):  
Resource Allocation ◽  
Sensor Network ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Network Environments

Visual sensor network lifetime maximization by prioritized scheduling of nodes

2013 ◽  
Vol 36 (1) ◽  
pp. 409-419 ◽  
Author(s):  
M. Hooshmand ◽  
S.M.R. Soroushmehr ◽  
P. Khadivi ◽  
S. Samavi ◽  
S. Shirani
Keyword(s):  
Sensor Network ◽  
Network Lifetime ◽  
Visual Sensor ◽  
Lifetime Maximization ◽  
Visual Sensor Network

Dynamic Resource Allocation for Compressive-Sensing-Based Wireless Visual Sensor Networks with Energy Harvesting

2013 ◽  
Vol 303-306 ◽  
pp. 187-190
Author(s):  
Lei You ◽  
Xin Su ◽  
Yu Tong Han
Keyword(s):  
Resource Allocation ◽  
Energy Harvesting ◽  
Compressive Sensing ◽  
Information Acquisition ◽  
Visual Information ◽  
Sensor Nodes ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Available Bandwidth ◽  
Potential Applications

Wireless visual sensor network (WVSN) is emerging with many potential applications. The lifetime of a WVSN is seriously dependent on the energy shored in the battery of its sensor nodes as well as the adopted compression and resource allocation scheme. In this paper, we use the energy harvesting to provide almost perpetual operation of the networks and compressed-sensing-based encoding to decrease the power consumption of acquiring visual information at the front-end sensors. We propose a dynamic algorithm to jointly allocate power for both compressive-sensing-based visual information acquisition and data transmission, as well as the available bandwidth under energy harvesting and stability constraints. A virtual energy queue is introduced to control the resource allocation and the measurement rate in each time slot. The algorithm can guarantee the stability of the visual data queues in all sensors and achieve near-optimal performance.

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