When camera-enabled sensors are deployed for visual monitoring, a new set of innovative applications is allowed, enriching the use of wireless sensor network technologies. In these networks, energy-efficiency is a highly desired optimization issue, mainly because transmission of images and video streams over resource-constrained sensor networks is more stringent than transmission of conventional scalar data. Due to the nature of visual monitoring, that follows a directional sensing model, camera-enabled sensors may have different relevancies for the application, according to the desired monitoring tasks and the current sensors’ poses and fields of view. Exploiting this concept, each data packet may be associated with a priority level related to the packet’s origins, which may be in turn mapped to an energy threshold level. In such way, we propose an energy-efficient relaying mechanism where data packets are only forwarded to the next hop if the associated energy threshold level is below the current energy level of the relaying node. Thus, packets from low-relevant source nodes will be silently dropped when the current energy level of intermediate nodes run below the pre-defined thresholds. Doing so, energy is saved potentially prolonging the network lifetime. Besides the sensing relevancies of source nodes, the relevance of DWT subbands for reconstruction of original images is also considered. This allows the creation of a second level of packet prioritization, assuring a minimal level of image quality even for the least relevant source nodes. We performed simulations for the proposed relaying mechanism, assessing the expected performance over a traditional relaying paradigm.
References
[1]
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.
[2]
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.
[3]
Soro, S.; Heinzelman, W. A survey of visual sensor networks. Adv. Multimed 2009, 2009, doi:10.1155/2009/640386.
Costa, D.; Guedes, L. The coverage problem in video-based wireless sensor networks: A survey. Sensors 2010, 10, 8215–8247, doi:10.3390/s100908215.
[6]
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.
[7]
Costa, D.; Guedes, L.; Vasques, F.; Portugal, P. Effect of Frame Size on Energy Consumption in Wireless Image Sensor Networks. In Proceedings of 2012 IEEE International Conference on Imaging Systems and Techniques (IST), Manchester, UK, 16–17 July 2012; pp. 239–244.
[8]
Qaisar, S.; Radha, H. Multipath Multi-stream Distributed Reliable Video Delivery in Wireless Sensor Networks. In Proceedings of 43rd Annual Conference on Proceeding of the Information Sciences and Systems, CISS 2009, Baltimore, MD, USA, 18–20 March 2009; pp. 207–212.
[9]
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, doi:10.1155/2007/47345.
[10]
Yaghmaee, M.; Adjeroh, D. A New Priority Based Congestion Control Protocol for Wireless Multimedia Sensor Networks. In Proceeding of the WoWMoM 2008. 2008 International Symposium on a World of WirelessMobile and Multimedia Networks, Newport Beach, CA, USA, 23–26 June 2008; pp. 1–8.
[11]
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.
[12]
Chen, B.; Jamieson, K.; Balakrishnan, H.; Morris, R. SPAN: An energy efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wirel Netw. 2002, 8, 481–494, doi:10.1023/A:1016542229220.
[13]
Costa, D.; Guedes, L. Exploiting the sensing relevancies of source nodes for optimizations in visual sensor networks. Multimed. Tools Appl. 2013, 64, 549–579, doi:10.1007/s11042-011-0961-4.
[14]
Chow, K.-Y.; Lui, K.-S.; Lam, E. Achieving 3600 Angle Coverage with Minimum Transmission Cost in Visual Sensor Networks. In Proceedings IEEE Wireless Communications and Networking Conference, Cancun, Mexico, 28–31 March 2011; pp. 4112–4116.
[15]
Ai, J.; Abouzeid, A. Coverage by directional sensors in randomly deployed wireless sensors networks. J. Comb. Optim. 2006, 11, 21–41, doi:10.1007/s10878-006-5975-x.
[16]
Politis, I.; Tsagkaropoulos, M.; Dagiuklas, T.; Kotsopoulos, S. Power efficient video multipath transmission over wireless multimedia sensor networks. Mob. Netw. Appl. 2008, 13, 274–284.
[17]
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.
[18]
Costa, D.; Guedes, L.; Vasques, F.; Portugal, P. Energy-Efficient Visual Monitoring Based on the Sensing Relevancies of Source Nodes for Wireless Image Sensor Networks. In Proceedings of IEEE Sensors Applications Symposium, Brescia, Italy, 7–9 February 2012; pp. 1–6.
[19]
Costa, D.; Guedes, L.; Vasques, F.; Portugal, P. A Semi-Reliable Energy-Efficient Retransmission Mechanism Based on the Sensing Relevancies of Source Nodes for Wireless Image Sensor Networks. In Proceedings of International Symposium on Wireless Communication Systems, Paris, France, 28–31 August 2012; pp. 506–510.
[20]
Maimour, M.; Pham, C.; Amelot, J. Load Repartition for Congestion Control in Multimedia Wireless Sensor Networks with Multipath Routing. In Proceedings of International Symposium on Wireless Pervasive Computing, Santorini, Greece, 7–9 May 2008; pp. 11–15.
[21]
Yu, W.; Sahinoglu, Z.; Vetro, A. Energy Efficient JPEG 2000 Image Transmission over Wireless Sensor Networks. In Proceedings of Globecom, Dallas, TX, USA, 29 November–3 December 2004; pp. 2738–2743.
[22]
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.
[23]
Zhang, L.; Hauswirth, M.; Shu, L.; Zhou, Z.; Reynolds, V.; Han, G. Multi-Priority Multi-Path Selection for Video Streaming in Wireless Multimedia Sensor Networks. In Proceedings of International Conference on Ubiquitous Intelligence and Computing, Oslo, Norway, 23–25 June 2008; pp. 439–452.
[24]
Costa, D.; Guedes, L. A discrete wavelet transform (DWT)-based energy-efficient selective retransmission mechanism for wireless image sensor networks. J. Sens. Actuator Netw. 2012, 1, 3–35, doi:10.3390/jsan1010003.
[25]
Dam, T.; Langendoe, K. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks. In Proceedings of ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 5–7 November 2003; pp. 171–180.
[26]
Heinzelman, W.; Chandrakasan, A.; Balakrishnan, H. An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wirel. Commun. 2002, 1, 660–670.
[27]
Bajaber, F.; Awan, I. Adaptive decentralized re-clustering protocol for wireless sensor networks. J. Comput. Syst. Sci. 2011, 77, 282–292, doi:10.1016/j.jcss.2010.01.007.
[28]
Korhonen, J.; Wang, Y. Effect of Packet Size on Loss Rate and Delay in Wireless Links. In Proceedings of the 2005 IEEE Wireless Communications and Networking Conference, New Orleans, LA, USA, 13–17 March 2005; pp. 1608–1613.
[29]
Pekhteryev, G.; Sahinoglu, Z.; Orlik, P.; Bhatti, G. Image Transmission over IEEE 802.15.4 and ZigBee Networks. In Proceeding of the IEEE International Symposium on Circuits and Systems, Kobe, Japan, 23–26 May 2005; pp. 539–3542.
[30]
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.
[31]
Lecuire, V.; Duran-Faundez, C.; Krommenacker, N. Energy-efficient image transmission in sensor networks. Int. J. Sens. Netw. 2008, 4, 37–47.
[32]
Latré, B.; Mil, P.; Moerman, I.; Dhoedt, B.; Demeester, P. Throughput and delay analysis of unslotted IEEE 802.15.4. J. Netw. 2006, 1, 20–28.
[33]
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:10.1145/1672308.1672311.
[34]
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.
[35]
Brooks, P.; Hestnes, B. User measures of quality of experience: Why being objective and quantitative is important. IEEE Netw. 2010, 24, 8–13, doi:10.1109/MNET.2010.5430138.
Tselishchev, Y.; Boulis, A.; Libman, L. Experiences and Lessons from Implementing a Wireless Sensor Network MAC Protocol in the Castalia Simulator. In Proceedings of the 2010 IEEE Wireless Communications and Networking Conference (WCNC), Sydney, Australia, 18–21 April 2010; pp. 1–6.
[38]
Costa, D.; Guedes, L.; Vasques, F.; Portugal, P. QoV: Assessing the Monitoring Quality in Visual Sensor Networks. In Proceedings of the2012 IEEE 8th International Conference on Wireless and Mobile ComputingNetworking and Communications (WiMob), Barcelona, Spain, 8–10 October 2012; pp. 667–674.
[39]
Tavli, B.; Bicakci, K.; Zilan, R.; Barcelo-Ordinas, J. A survey of visual sensor network platforms. Multimed. Tools Appl. 2012, 60, 689–726, doi:10.1007/s11042-011-0840-z.
[40]
Seema, A.; Reisslein, M. Towards efficient wireless video sensor networks: A survey of existing node architectures and proposal for A Flexi-WVSNP design. IEEE Commun. Surv. Tut. 2011, 13, 462–486, doi:10.1109/SURV.2011.102910.00098.
[41]
Rein, S.; Reisslein, M. Low-memory wavelet transforms for wireless sensor networks: A tutorial. IEEE Commun. Surv. Tut. 2011, 13, 291–307, doi:10.1109/SURV.2011.100110.00059.
