Source nodes in wireless image sensor networks transmit much more information than traditional scalar sensor networks, thereby demanding more energy of intermediate relaying nodes and putting energy efficiency as a key design issue. Intermediate nodes are usually interconnected by error-prone links where bit-errors are common, potentially degrading the application monitoring quality. When reliability is assured by retransmission mechanisms, higher packet error rates do not affect the application quality but result in additional energy consumption due to packet retransmission, even though many monitoring applications can tolerate some loss in the quality of the received image. DWT coding can decompose an image in data subbands, each one with different relevancies for the reconstruction of the original image at the receiver side. We propose an energy-efficient selective hop-by-hop retransmission mechanism where the reliability level of each packet is a function of the relevance of the payload data, according to the resulting subbands and the number of times a 2D DWT is applied over the images captured by the sensors’ cameras. In so doing, some lost packets are not retransmitted, saving energy of intermediate nodes with low impact to the quality of the reconstructed images. In order to estimate the benefits of this tradeoff between energy consumption and image quality, we designed a comprehensive energy consumption model and applied it in extensive mathematic simulations, providing substantial information about the mean performance of the proposed approach when compared with a fully-reliable transmission mechanism.
Akyildiz, I.; Su, W.; Sankarasubramaniam, Y.; Cayirci, E. Wireless sensor networks: A survey. Comput. Netw. 2002, 38, 393–422, doi:10.1016/S1389-1286(01)00302-4.
[3]
Baronti, P.; Pillai, P.; Chook, V.; Chessa, S.; Gotta, A.; Hu, Y. Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 2006, 30, 1655–1695.
[4]
Almalkawi, I.; Zapata, M.; Al-Karaki, J.; Morillo-Pozo, J. Wireless multimedia sensor networks: Current trends and future directions. Sensors 2010, 10, 6662–6717, doi:10.3390/s100706662.
[5]
Misra, S.; Reisslein, M.; Xue, G. A survey of multimedia streaming in wireless sensor networks. IEEE Commun. Surv. Tutor. 2009, 10, 18–39.
[6]
Soro, S.; Heinzelman, W. On the Coverage Problem in Video-Based Wireless Sensor Networks. In Proceedings of the International Conference on Broadband Networks, Boston, MA, USA, 3–7 October 2005; pp. 932–939.
[7]
Soro, S.; Heinzelman, W. A survey of visual sensor networks. Adv. Multimed. 2009, 2009, 1–21.
Costa, D.; Guedes, L. The coverage problem in video-based wireless sensor networks: A survey. Sensors 2010, 10, 8215–8247, doi:10.3390/s100908215.
[10]
Costa, D.; Guedes, L. A survey on multimedia-based cross-layer optimization in visual sensor networks. Sensors 2011, 11, 5439–5468, doi:10.3390/s110505439.
[11]
Akyildiz, I.; Melodia, T.; Chowdhury, K. A survey on wireless multimedia sensor networks. Comput. Netw. 2007, 51, 921–960, doi:10.1016/j.comnet.2006.10.002.
[12]
Boukerche, A.; Du, Y.; Feng, J.; Pazzi, R. A Reliable Synchronous Transport Protocol for Wireless Image Sensor Networks. In Proceedings of IEEE Symposium on Computers and Communications, Marrakesh, Morocco, 6–9 July 2008; pp. 1083–1089.
[13]
Stann, F.; Heidemann, J. RMST: Reliable Data Transport in Sensor Networks. In Proceedings of International Workshop on Sensor Network Protocols and Applications, Anchorage, AK, USA, 11 May 2003; pp. 102–112.
[14]
Liu, Y.; Huang, H.; Xu, K. Multi-path-based Distributed TCP Caching for Wireless Sensor Networks. In Proceedings of International Conference on Software EngineeringArtificial IntelligenceNetworking and Parallel/Distributed Computing, Phuket, Thailand, 6–8 August 2007; pp. 331–335.
[15]
Wu, H.; Abouzeid, A. Error resilient image transport in wireless sensor networks. Comput. Netw. 2006, 50, 2873–2887, doi:10.1016/j.comnet.2005.09.039.
[16]
Lecuire, V.; Duran-Faundez, C.; Krommenacker, N. Energy-efficient transmission of wavelet-based images in wireless sensor networks. EURASIP J. Image Video Process. 2007, 2007, 1–11.
[17]
Lee, J.-H.; Jun, I.-B. Adaptive-compression based congestion control technique for wireless sensor networks. Sensors 2010, 10, 2919–2945, doi:10.3390/s100402919.
[18]
Dam, T.; Langendoe, K. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks. In Proceedings of ACM SenSys, Los Angeles, CA, USA, 5–7 November 2003; pp. 1–10.
[19]
Korhonen, J.; Wang, Y. Effect of Packet Size on Loss Rate and Delay in Wireless Links. In Proceedings of IEEE Wireless Communications and Networking Conference, New Orleans, FL, USA, 13–17 March 2005; pp. 1608–1613.
[20]
Pekhteryev, G.; Sahinoglu, Z.; Orlik, P.; Bhatti, G. Image Transmission over IEEE 802.15.4 and ZigBee Networks. In Proceedings of IEEE International Symposium on Circuits and Systems, Kobe, Japan, 23–26 May 2005; pp. 539–3542.
[21]
Lecuire, V.; Duran-Faundez, C.; Krommenacker, N. Energy-efficient image transmission in sensor networks. Int. J. Sens. Netw. 2008, 4, 37–47, doi:10.1504/IJSNET.2008.019250.
[22]
Qaisar, S.; Radha, H. Multipath Multi-stream Distributed Reliable Video Delivery in Wireless Sensor Networks. In Proceedings of Conference of Information Sciences and Systems, Baltimore, MA, USA, 18–20 March 2009; pp. 207–212.
[23]
Liang, Y.; Peng, W. Minimizing energy consumptions in Wireless sensor networks via two-modal transmission. ACM SIGCOMM Comput. Commun. Rev. 2010, 40, 12–18, doi:10.1145/1764873.1764876.
[24]
Demirkol, I.; Ersoy, C.; Alag？z, F. MAC protocols for wireless sensor networks: A survey. IEEE Commun. Mag. 2006, 44, 115–121.
[25]
Garcia-Sanchez, A.-J.; Garcia-Sanchez, F.; Garcia-Haro, J.; Losilla, F. A cross-layer solution for enabling real-time video transmission over IEEE 802.15.4 networks. Multim. Tools App. 2011, 51, 1069–1104, doi:10.1007/s11042-010-0460-z.
[26]
Han, B.; Lee, S. Efficient Packet Error Rate Estimation in Wireless Networks. In Proceedings of Conference on Testbeds and Research Infrastructure for the Development of Networks and Communities, Orlando, FL, USA, 21–23 May 2007; pp. 1–9.
[27]
Dunkels, A.; Alonso, J.; Voigt, T.; Ritter, H. Distributed TCP Caching for Wireless Sensor Networks. In Proceedings of Annual Mediterranean Ad Hoc Networking Workshop, Bodrum, Turkey, 27–30 June 2004; pp. 1–11.
[28]
Shon, T.; Choi, H. Towards the implementation of reliable data transmission for 802.15.4-based wireless sensor networks. Lecture Notes Comput. Sci. 2008, 5061, 363–372, doi:10.1007/978-3-540-69293-5_29.
[29]
Chew, L.; Ang, L.-M.; Seng, K. Survey of Image Compression Algorithms in Wireless Sensor Networks. In Proceedings of International Symposium on Information Technology, Kuala Lumpur, Malaysia, 26–28 August 2008; pp. 1–9.
[30]
Antonini, M.; Barlaud, M.; Mathieu, P.; Daubechies, I. Image coding using wavelet transform. IEEE Trans. Image Process. 1992, 1, 205–220, doi:10.1109/83.136597.
[31]
Lee, D.; Dey, S. Adaptive and Energy Efficient Wavelet Image Compression for Mobile Multimedia Data Services. In Proceedings of IEEE International Conference on Communications, New York, USA, 28 April-2 May 2002; pp. 2484–2490.
[32]
Duran-Faundez, C.; Lecuire, V.; Lepage, F. Tiny block-size coding for energy-efficient image compression and communication in wireless camera sensor networks. Signal Process. Image Commun. 2011, 26, 466–481, doi:10.1016/j.image.2011.07.005.
