Energy-Aware Video Coding Selection for Solar-Powered Wireless Video Sensor Networks
2017, 22(7), pp.101-108
DOI :https://doi.org/10.9708/jksci.2017.22.07.101
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
-
A wireless image sensor node collecting image data for environmental monitoring or surveillance requires a large amount of energy to transmit the huge amount of video data. Even though solar energy can be used to overcome the energy constraint, since the collected energy is also limited, an efficient energy management scheme for transmitting a large amount of video data is needed. In this paper, we propose a method to reduce the number of blackout nodes and increase the amount of gathered data by selecting an appropriate video coding method according to the energy condition of the node in a solar-powered wireless video sensor network. This scheme allocates the amount of energy that can be used over time in order to seamlessly collect data regardless of night or day, and selects a high compression coding method when the allocated energy is large and a low compression coding when the quota is low. Thereby, it reduces the blackout of the relay node and increases the amount of data obtained at the sink node by allowing the data to be transmitted continuously. Also, if the energy is lower than operating normaly, the frame rate is adjusted to prevent the energy exhaustion of nodes. Simulation results show that the proposed scheme suppresses the energy exhaustion of the relay node and collects more data than other schemes.
-
[journal] IF. Akyildiz / 2007 / A Survey on Wireless Multimedia Sensor Networks / Computer networks 51 (4) : 921~960
[journal] S. Misra / 2008 / A Survey of Multimedia Streaming in Wireless Sensor Networks / IEEE communications surveys & tutorials 10 (4) : 18~39
[journal] IF. Akyildiz / 2007 / Wireless Multimedia Sensor Networks : A Survey / IEEE Wireless Communications 14 (6) : 32~39
[journal] S. Sudevalayam / 2011 / Energy Harvesting Sensor Nodes : Survey and Implications / Communications Surveys & Tutorials, IEEE 13 (3) : 443~461
[thesis] S. J. Roundy / 2003 / Energy Scavenging for Wireless Sensor Nodes with a Focus on Vibration to Electricity Conversion / Ph.D / University of California
[journal] H. Yoo / 2012 / Dynamic Duty-Cycle Scheduling Schemes for Energy-Harvesting Wireless Sensor Networks / IEEE communications letters 16 (2) : 202~204
[journal] RJM. Vullers / 2010 / Energy Harvesting for Autonomous Wireless Sensor Networks / IEEE Solid-State Circuits Magazine 2 (2) : 29~38
[book] S. Basagni / 2013 / Mobile Ad Hoc Networking: The Cutting Edge Directions / Wiley : 701~736
[confproc] A. Luthra / 2003 / Overview of the H. 264/AVC video coding standard / Proceedings of the 48th SPIE's Optical Science and Technology International Society for Optics and Photonics : 417~431
[confproc] T. Fukuhara / 2000 / Motion-JPEG2000 standardization and target market / Preceedings of the International Conference on Image Processing 57 (60) : 57~60
[journal] GJ. Sullivan / 2012 / Overview of The High Efficiency Video Coding(HEVC)Standard / IEEE Trans. on circuits and systems for video technology 22 (12) : 1649~1668
[confproc] J. J. Ahmad / 2009 / Energy effivient video compression for wireless sensor networks / Proceedings of the 43rd Annual Conference on Information Sciences and System(CISS) : 629~634
[journal] R. Puri / 2006 / Distributed Video Coding in Wireless Sensor Networks / IEEE Signal Processing Magazine 23 (4) : 94~106
[confproc] E. Magli / 2003 / Low-complexity video compression for wireless sensor networks / Proceedings of the International Conference on Multimedia and Expo 585 (588) : 2003~
[journal] Z. Xiong / 2004 / Distributed Source Coding for Sensor Networks / IEEE signal processing magazine 21 (5) : 80~94
[journal] S. Pudlewski / 2012 / Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks / IEEE Trans. on Mobile Computing 11 (6) : 1060~1072
[confproc] M. Magno / 2008 / A solar-powered video sensor node for energy efficient multimodal surveillance / Proceedings of the 11st EUROMICRO Conference on Digital System Design Architectures, Methods and Tools : 512~519
[confproc] T. H. Nguyen / 2017 / Joint time switching and rate allocation optimization for energy efficiency in wireless multimedia sensor networks / Proceedings of the 2017 International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom) : 175~180
[journal] A. Arar / 2017 / Optimal Resource Allocation for Green and Clustered Video Sensor Networks / IEEE Systems Journal PP (99) : 1~12
[confproc] A. A. El-Sherif / 2013 / Optimum power and rate allocation in video sensor networks / Proceedings of the 2013 IEEE Global Communications Conference (GLOBECOM) : 480~486
[journal] S. H. Ou / 2015 / On-Line Multi-View Video Summarization for Wireless Video Sensor Network / IEEE Journal of Selected Topics in Signal Processing 9 (1) : 165~179
[confproc] A. Cammarano / 2012 / Pro-energy : A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks / Proceedings of the 9th International Conference on Mobile Adhoc and Sensor Systems : 75~83
[journal] D. K. Noh / 2011 / Balanced Energy Allocation Scheme for A Solar-Powered Sensor System and Its Effects on Network-Wide Performance / Journal of Computer and System Sciences 77 (5) : 917~932
[confproc] Y. Yang / 2009 / Solarstore : enhancing data reliability in solar-powered storage-centric sensor networks / Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services (MobiSys) : 333~346
[journal] J. Yi / 2015 / SolarCastalia : Solar Energy Harvesting Wireless Sensor Network Simulator / International Journal of Distributed Sensor Networks 2015 : 10~
-
KCI Citation (0)
178
Viewed
Print this page
Download PDF