Video sensor node energy preservation through dynamic adaptive video encoding parameters' values selection

Abstract Wireless video sensor networks (WVSN) are energy constrained systems where deployed video nodes are capable of capturing the visual scene, performing local processing such as video compression, then routing the results toward the destination. In this paper, we consider the problem of minimizing the energy consumed by the video sensor node to encode and transmit the video stream under a defined video quality constraint. In the present work, Intra-Only H.264/AVC is considered as video compression scheme. Particularly, we propose to control at run-time both the energies consumed for video encoding and transmitting, in addition to the video encoding distortion. Thus, we begin our study by profiling the evolution of these quantities according to two coding parameters, namely the frame rate (FR) and the quantization parameter (QP). Following an analysis of the obtained measurements, we propose empirical parametric models in line with the observed behaviors, then validate them with different video sequences. Finally, we introduce the Dynamic Adaptive Encoding Parameters’ values Selection (DAEPS) procedure which relies on these models to solve the problem under consideration. Simulations show the advantage of considering such an approach, which is capable, on the one hand, of extending the lifetime of the video sensor node up to 2.3 times, when compared with state-of-the-art approaches, and on the other hand, of complying with the defined end-to-end video quality constraint.

[1]  Hamid Sharif,et al.  A Survey of Energy-Efficient Compression and Communication Techniques for Multimedia in Resource Constrained Systems , 2013, IEEE Communications Surveys & Tutorials.

[2]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[3]  Djamel Djenouri,et al.  Congestion Control Protocols in Wireless Sensor Networks: A Survey , 2014, IEEE Communications Surveys & Tutorials.

[4]  Liudong Xing,et al.  Hybrid wireless sensor networks: a reliability, cost and energy-aware approach , 2016, IET Wirel. Sens. Syst..

[5]  Aliaa A. A. Youssif,et al.  ACWSN: an adaptive cross layer framework for video transmission over wireless sensor networks , 2015, Wireless Networks.

[6]  Syed Ali Khayam,et al.  Energy efficient video compression for wireless sensor networks , 2009, 2009 43rd Annual Conference on Information Sciences and Systems.

[7]  Ian F. Akyildiz,et al.  Correlation-Aware QoS Routing With Differential Coding for Wireless Video Sensor Networks , 2012, IEEE Transactions on Multimedia.

[8]  Aliaa A. A. Youssif,et al.  Energy Aware and Adaptive Cross-Layer Scheme for Video Transmission Over Wireless Sensor Networks , 2016, IEEE Sensors Journal.

[9]  Geoffrey Ye Li,et al.  A survey of energy-efficient wireless communications , 2013, IEEE Communications Surveys & Tutorials.

[10]  MengChu Zhou,et al.  Recent Advances in Energy-Efficient Routing Protocols for Wireless Sensor Networks: A Review , 2016, IEEE Access.

[11]  Xiaolan Liu A Survey on Wireless Camera Sensor Networks , 2014 .

[12]  Ridha Bouallegue,et al.  Medium Access Control (MAC) Protocols for Wireless Sensor Network: An Energy Aware Survey , 2016 .

[13]  Fernando J. Velez,et al.  Survey on the Characterization and Classification of Wireless Sensor Network Applications , 2014, IEEE Communications Surveys & Tutorials.

[14]  Wendi B. Heinzelman,et al.  A Survey of Visual Sensor Networks , 2009, Adv. Multim..

[15]  Hong-Hsu Yen,et al.  A Survey on Sensor Coverage and Visual Data Capturing/Processing/Transmission in Wireless Visual Sensor Networks , 2014, Sensors.

[16]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[17]  Sebnem Baydere,et al.  Perceptual quality-based image communication service framework for wireless sensor networks , 2014, Wirel. Commun. Mob. Comput..

[18]  Qing Chen,et al.  Energy-efficient modulation design for reliable communication in wireless networks , 2009, 2009 43rd Annual Conference on Information Sciences and Systems.

[19]  Tarek R. Sheltami,et al.  Data compression techniques in Wireless Sensor Networks , 2016, Future Gener. Comput. Syst..

[20]  Driss Aboutajdine,et al.  Energy efficient adaptive video compression scheme for WVSNs , 2013, 21st European Signal Processing Conference (EUSIPCO 2013).

[21]  Driss Aboutajdine,et al.  Increasing network lifetime in an energy-constrained wireless sensor network , 2013, Int. J. Sens. Networks.

[22]  Xuxun Liu,et al.  A Survey on Clustering Routing Protocols in Wireless Sensor Networks , 2012, Sensors.

[23]  Kaibin Huang,et al.  Energy Harvesting Wireless Communications: A Review of Recent Advances , 2015, IEEE Journal on Selected Areas in Communications.

[24]  Taejoon Kim,et al.  Physical Layer and Medium Access Control Design in Energy Efficient Sensor Networks: An Overview , 2015, IEEE Transactions on Industrial Informatics.

[25]  Adel Ali Ahmed,et al.  An optimal complexity H.264/AVC encoding for video streaming over next generation of wireless multimedia sensor networks , 2016, Signal Image Video Process..

[26]  Ian F. Akyildiz,et al.  Wireless multimedia sensor networks: A survey , 2007, IEEE Wireless Communications.

[27]  Driss Aboutajdine,et al.  Energy consumption analysis and modelling of a H.264/AVC intra-only based encoder dedicated to WVSNs , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[28]  Driss Aboutajdine,et al.  Energy-efficient joint video encoding and transmission framework for WVSN , 2018, Multimedia Tools and Applications.

[29]  Chenyang Lu,et al.  Energy-efficient Low Power Listening for wireless sensor networks in noisy environments , 2013, 2013 ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[30]  Olivier Berder,et al.  FTA-MAC: Fast Traffic Adaptive Energy Efficient MAC Protocol for Wireless Sensor Networks , 2016, CrownCom.

[31]  Dimitrios D. Vergados,et al.  Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey , 2013, IEEE Communications Surveys & Tutorials.