QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices
Over the last couple of years, video service distribution among smart phones and other mobile video devices is becoming increasingly popular in sensor networks. However, the huge energy consumption caused by video encoding and transmitting and the slowly evolving battery technologies become the majo...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-09-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/980174 |
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| _version_ | 1832547209720102912 |
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| author | Zhaoming Lu Hongchun Zhang Yawen Chen Hua Shao Xiangming Wen |
| author_facet | Zhaoming Lu Hongchun Zhang Yawen Chen Hua Shao Xiangming Wen |
| author_sort | Zhaoming Lu |
| collection | DOAJ |
| description | Over the last couple of years, video service distribution among smart phones and other mobile video devices is becoming increasingly popular in sensor networks. However, the huge energy consumption caused by video encoding and transmitting and the slowly evolving battery technologies become the major bottlenecks that hinder the development of video streaming services. Hence energy efficient video coding and transmitting solutions are required to be investigated. Yet, energy consumption reduction of mobile video devices will be accompanied with Quality of Experience (QoE) degradation of video applications. Such diverse tendency makes it difficult to encode and transmit video streams with less energy as well as better QoE. This paper analyzes the major energy consuming factors in mobile video devices. A specific energy consumption model concerning encoding bitrates and transmitting power level is built. Further, a noninvasive QoE perceptive model is adopted so that the energy efficiency problem becomes a cross-layer optimization problem. Chaos particle swarm optimization is used to solve this cross-layer optimization problem with fast convergence. By this method, energy consumption of mobile video device is minimized with acceptable QoE for video users. At last, Pareto front of energy and QoE is analyzed to certify the performance of our method. |
| format | Article |
| id | doaj-art-33c3cf40ea304b4dabc72062e89429ba |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-33c3cf40ea304b4dabc72062e89429ba2025-02-03T06:45:29ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-09-011110.1155/2015/980174980174QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video DevicesZhaoming LuHongchun ZhangYawen ChenHua ShaoXiangming WenOver the last couple of years, video service distribution among smart phones and other mobile video devices is becoming increasingly popular in sensor networks. However, the huge energy consumption caused by video encoding and transmitting and the slowly evolving battery technologies become the major bottlenecks that hinder the development of video streaming services. Hence energy efficient video coding and transmitting solutions are required to be investigated. Yet, energy consumption reduction of mobile video devices will be accompanied with Quality of Experience (QoE) degradation of video applications. Such diverse tendency makes it difficult to encode and transmit video streams with less energy as well as better QoE. This paper analyzes the major energy consuming factors in mobile video devices. A specific energy consumption model concerning encoding bitrates and transmitting power level is built. Further, a noninvasive QoE perceptive model is adopted so that the energy efficiency problem becomes a cross-layer optimization problem. Chaos particle swarm optimization is used to solve this cross-layer optimization problem with fast convergence. By this method, energy consumption of mobile video device is minimized with acceptable QoE for video users. At last, Pareto front of energy and QoE is analyzed to certify the performance of our method.https://doi.org/10.1155/2015/980174 |
| spellingShingle | Zhaoming Lu Hongchun Zhang Yawen Chen Hua Shao Xiangming Wen QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices International Journal of Distributed Sensor Networks |
| title | QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices |
| title_full | QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices |
| title_fullStr | QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices |
| title_full_unstemmed | QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices |
| title_short | QoE Perceptive Cross-Layer Energy Efficient Method for Mobile Video Devices |
| title_sort | qoe perceptive cross layer energy efficient method for mobile video devices |
| url | https://doi.org/10.1155/2015/980174 |
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