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

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

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

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.


    1. 1)
      • 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).
    2. 2)
    3. 3)
    4. 4)
    5. 5)
      • 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. 263268.
    6. 6)
      • 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. 69356940.
    7. 7)
    8. 8)
      • 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. 112.
    9. 9)
      • 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. 10521056.
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
      • 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. 342346.
    15. 15)
      • 15. Chou, P.A., Wang, H.J., Padmanabhan, V.N.: ‘Layered multiple description coding’. Proc. Packet Video Workshop, 2003, pp. 17.
    16. 16)
    17. 17)
    18. 18)
    19. 19)
    20. 20)
      • 20. Hou, Y.T., Shi, Y., Sherali, H.D.: ‘Applied optimization methods for wireless networks’ (Cambridge University Press, New York, 2013, 1st edn.).
    21. 21)
      • 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. 63246330.
    22. 22)
      • 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. 126134.
    23. 23)
    24. 24)
      • 24. Goldberg, D.E.: ‘Genetic algorithms in search, optimization, and machine learning’ (Addison-Wesley Press, Reading, MA, 1988).
    25. 25)
    26. 26)
      • 26. ‘HM Reference Software Version 12.0’. Available at

Related content

This is a required field
Please enter a valid email address