Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework

Nguyen-Son Vo; Dac-Binh Ha; Berk Canberk; Junqing Zhang

Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework

View Fulltext

Author(s): Nguyen-Son Vo ¹ ; Dac-Binh Ha ¹ ; Berk Canberk ² ; Junqing Zhang ³
- Affiliations: 1: Faculty of Electrical and Electronics Engineering, Duy Tan University, Da Nang, Vietnam ;
  2: Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey ;
  3: School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, UK
Source: Volume 10, Issue 18, 15 December 2016, p. 2543 – 2550
DOI: 10.1049/iet-com.2016.0406 , Print ISSN 1751-8628, Online ISSN 1751-8636

Received 01/04/2016, Accepted 10/06/2016, Revised 02/06/2016, Published 15/12/2016

In wireless multimedia sensor systems (WMSSs), the devices are equipped with multiple energy-constrained camera sensors (CSs) distributed over bandwidth-constrained and lossy wireless channels, in catastrophe-prone areas. Meanwhile, multimedia applications, e.g. video streaming, require considerable energy and bandwidth resources to gain long lifetime and high streaming quality. This study proposes an energy, bandwidth, and quality (EBQ) optimisation framework for green two-tiered WMSSs. The first tier contains the CSs and the second tier includes cluster heads (CHs) selected from the CSs with higher available energy and processing capacity. In the EBQ optimisation framework, a rate allocation optimisation problem is formulated under given constraints of available backhaul bandwidth of the CHs and quality of received videos at base stations (BSs). This problem is solved for optimal encoding rates to packetise each video captured from different environments into multiple descriptions for transmission. Consequently, the average energy consumption per CS is minimised for long lifetime while conserving the bandwidth of the CHs and guaranteeing high quality of received videos for the purpose of monitoring at the BSs. Simulations demonstrate that the proposed EBQ optimisation framework can efficiently enhance the performance of green two-tiered WMSSs in terms of minimum energy consumption, bandwidth efficiency, and high quality.

References

1. 1)
  - 3. Chen, J., Zhang, L., Kuo, Y.: ‘Coverage-enhancing algorithm based on overlap-sense ratio in wireless multimedia sensor networks’, IEEE Sens. J., 2013, 13, (6), pp. 2077–2083 (doi: 10.1109/JSEN.2013.2248144).
2. 2)
  - 13. Albanese, A., Blomer, J., Edmonds, J., et al: ‘Priority encoding transmission’, IEEE Trans. Inform. Theory, 1996, 42, (6), pp. 1737–1744 (doi: 10.1109/18.556670).
3. 3)
  - 6. Spachos, P., Toumpakaris, D., Hatzinakos, D.: ‘QoS and energy-aware dynamic routing in wireless multimedia sensor networks’. Proc. IEEE ICC, London, UK, June 2015, pp. 6935–6940.
4. 4)
  - 24. Goldberg, D.E.: ‘Genetic algorithms in search, optimization, and machine learning’ (Addison-Wesley Press, Reading, MA, 1988).
5. 5)
  - 1. Rao, R.R., Eisenberg, J., Schmitt, T.: ‘Improving disaster management: the role of IT in mitigation, preparedness, response, and recovery’ (The National Academies Press, Washington, DC, 2007).
6. 6)
  - 10. He, Z., Liang, Y., Chen, L., et al: ‘Power-rate-distortion analysis for wireless video communication under energy constraints’, IEEE Trans. Circuits Syst. Video Technol., 2005, 15, (5), pp. 645–658 (doi: 10.1109/TCSVT.2005.846433).
7. 7)
  - 8. Cheng, L., Niu, J., Francesco, M.D., et al: ‘Seamless streaming data delivery in cluster-based wireless sensor networks with mobile elements’, IEEE Sens. J., 2015, PP, (99), pp. 1–12.
8. 8)
  - 5. Spachos, P., Marnerides, A.K., Hatzinakos, D.: ‘Content relevance opportunistic routing for wireless multimedia sensor networks’. Proc. IEEE INFOCOM, Computer Communications Workshops, Toronto, Canada, April 2014, pp. 263–268.
9. 9)
  - 16. Du, X., Vo, N.-S., Cheng, W., et al: ‘Joint replication density and rate allocation optimization for VoD systems over wireless mesh networks’, IEEE Trans. Circuits Syst. Video Technol., 2013, 23, (7), pp. 1260–1273 (doi: 10.1109/TCSVT.2013.2242639).
10. 10)
  - 2. Baccarelli, E., Chiti, F., Cordeschi, N., et al: ‘Green multimedia wireless sensor networks: distributed intelligent data fusion, in-network processing, and optimized resource management’, IEEE Wirel. Commun., 2014, 21, (4), pp. 20–26 (doi: 10.1109/MWC.2014.6882292).
11. 11)
  - 22. Breslau, L., Cao, P., Fan, L., et al: ‘Web caching and Zipf-like distributions: evidence and implications’. Proc. IEEE INFOCOM, New York, NY, March 1999, pp. 126–134.
12. 12)
  - 11. Wang, W., Hempel, M., Peng, D., et al: ‘On energy efficient encryption for video streaming in wireless sensor networks’, IEEE Trans. Multimed., 2010, 12, (5), pp. 417–426 (doi: 10.1109/TMM.2010.2050653).
13. 13)
  - 14. Puri, R., Ramchandran, K.: ‘Multiple description source coding using forward error correction codes’. Proc. 33rd Asilomar Conf. on Signals, Systems and Computers, October 1999, pp. 342–346.
14. 14)
  - 7. Yao, R., Wang, W., Farrokh-Baroughi, M., et al: ‘Quality-driven energy-neutralized power and relay selection for smart grid wireless multimedia sensor based IoTs’, IEEE Sens. J., 2013, 13, (10), pp. 3637–3644 (doi: 10.1109/JSEN.2013.2262270).
15. 15)
  - 21. Zhang, R., Timmons, N., Morrison, J.: ‘Utility energy-based opportunistic routing for lifetime enhancement in wireless sensor networks’. Proc. IEEE ICC, London, UK, June 2015, pp. 6324–6330.
16. 16)
  - 23. Everett, H.: ‘Generalized Lagrange multiplier method for problems of optimum allocation of resources’, Oper. Res., 1963, 11, (13), pp. 399–417 (doi: 10.1287/opre.11.3.399).
17. 17)
  - 19. Li, X., Zhou, F., Du, J.: ‘LDTS: a lightweight and dependable trust system for clustered wireless sensor networks’, IEEE Trans. Inf. Forensics Sec., 2013, 8, (6), pp. 924–935 (doi: 10.1109/TIFS.2013.2240299).
18. 18)
  - 17. Boyce, J.M., Ye, Y., Chen, J., et al: ‘Overview of SHVC: scalable extensions of the high efficiency video coding standard’, IEEE Trans. Circuits Syst. Video Technol., 2016, 26, (1), pp. 20–34 (doi: 10.1109/TCSVT.2015.2461951).
19. 19)
  - 25. Fang, T., Chau, L.-P.: ‘GOP-based channel rate allocation using genetic algorithm for scalable video streaming over error-prone networks’, IEEE Trans. Image Process., 2006, 15, (6), pp. 1323–1330 (doi: 10.1109/TIP.2005.864159).
20. 20)
  - 18. Xiang, W., Zhu, C., Siew, C.K., et al: ‘Forward error correction-based 2-D layered multiple description coding for error-resilient H.264 SVC video transmission’, IEEE Trans. Circuits Syst. Video Technol., 2009, 19, (12), pp. 1730–1738 (doi: 10.1109/TCSVT.2009.2022787).
21. 21)
  - 20. Hou, Y.T., Shi, Y., Sherali, H.D.: ‘Applied optimization methods for wireless networks’ (Cambridge University Press, New York, 2013, 1st edn.).
22. 22)
  - 26. ‘HM Reference Software Version 12.0’. Available at http://hevc.hhi.fraunhofer.de.
23. 23)
  - 9. Hao, H., Wang, K., Ji, H., et al: ‘Utility-based scheduling algorithm for wireless multi-media sensor networks’. Proc. IEEE Personal, Indoor, and Mobile Radio Communications, Hong Kong, August 2015, pp. 1052–1056.
24. 24)
  - 12. Zou, J., Xiong, H., Li, C., et al: ‘Lifetime and distortion optimization with joint source/channel rate adaptation and network coding-based error control in wireless video sensor networks’, IEEE Trans. Veh. Technol., 2011, 60, (3), pp. 1182–1194 (doi: 10.1109/TVT.2011.2111425).
25. 25)
  - 15. Chou, P.A., Wang, H.J., Padmanabhan, V.N.: ‘Layered multiple description coding’. Proc. Packet Video Workshop, 2003, pp. 1–7.
26. 26)
  - 4. Priyadarshini, S.B.B., Panigrahi, S.: ‘Centralised cum sub-centralised scheme for multi-event coverage and optimum camera activation in wireless multimedia sensor networks’, IET Netw., 2015, 4, (6), pp. 314–328 (doi: 10.1049/iet-net.2015.0017).

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework

References

Related content