Joint Energy Sustainability and Quality of Service Framework Providing Soft Guarantees for Energy Harvesting Wireless Mesh Networks

  • Hadi Barghi
  • Seyed Vahid AzhariEmail author


We propose a framework of joint energy sustainability and QoS provisioning for energy harvesting Wireless Mesh Networks (WMN) equipped with battery. We consider end-to-end delay and throughput as QoS parameters in the proposed framework. Our framework extends the concept of virtualization to energy resources of a node and dedicates a virtual battery to each connection independently. More importantly, we present a novel approach for coupling delay and throughput requirements to their equivalent virtual battery specification, providing a trade-off between QoS and energy characteristics of a connection. Furthermore, we propose admission tests based on average and instantaneous energy requirements of a connection in relation to its QoS needs. These admission tests ensure an end-to-end soft delay bound which according to our simulations, is violated by merely 2%. Using our framework we also show the strikingly different energy policies that should be adopted for routing interactive and streaming as well as bursty and constant bit-rate applications over energy harvesting WMNs. Obtaining an upper bound on the amount of energy resources required within any network clique, we show how energy constrained networks can benefit from increasing transmission power or even reduced bit-rates, despite intuition. All our claims and discussions are backed both by simulations and analysis.


Wireless mesh networks Energy sustainability Energy harvesting Virtual battery IEEE 802.11s Quality of service Carrier sense 



  1. 1.
    Cai, L. X., Liu, Y., Luan, T. H., Shen, X., Mark, J. W., & Vincent Poor, H. (2014). Sustainability analysis and resource management for wireless mesh networks with renewable energy supplies. IEEE Journal on Selected Areas in Communications, 32(2), 345–355.CrossRefGoogle Scholar
  2. 2.
    Li, M., Nishiyama, H., Kato, N., Owada, Y., & Hamaguchi, K. (2015). On the energy-efficient of throughput-based scheme using renewable energy for wireless mesh networks in disaster area. IEEE Transactions on Emerging Topics in Computing, 3(3), 420–431.CrossRefGoogle Scholar
  3. 3.
    Luo, C., Guo, S., Guo, S., Yang, L. T., Min, G., & Xie, X. (2014). Green communication in energy renewable wireless mesh networks: Routing, rate control, and power allocation. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3211–3220.CrossRefGoogle Scholar
  4. 4.
    Zhou, L., Kang, G., Zhang, N., & Cheng, J. (2015). Spectral efficiency guaranteed sustainable routing for energy renewable wireless mesh networks. In International conference on wireless communications & signal processing (WCSP) (pp. 1–5). IEEE.Google Scholar
  5. 5.
    Cao, Q., Fesehaye, D., Pham, N., Sarwar, Y., & Abdelzaher, T. (2008). Virtual battery: An energy reserve abstraction for embedded sensor networks. In Real-time systems symposium (pp. 123–133). IEEE.Google Scholar
  6. 6.
    Georgiadis, L., Guérin, R., Peris, V., & Sivarajan, K. N. (1996). Efficient network QoS provisioning based on per node traffic shaping. IEEE/ACM Transactions on Networking (TON), 4(4), 482–501.CrossRefGoogle Scholar
  7. 7.
    Crenshaw, T. L., Hoke, S., Tirumala, A., & Caccamo, M. (2007). Robust implicit edf: A wireless mac protocol for collaborative real-time systems. ACM Transactions on Embedded Computing Systems (TECS), 6(4), 28.CrossRefGoogle Scholar
  8. 8.
    Jayachandran, P., & Andrews, M. (2010). Minimizing end-to-end delay in wireless networks using a coordinated edf schedule. In Proceedings IEEE INFOCOM (pp 1–9). IEEE.Google Scholar
  9. 9.
    El Korbi, I., & Azouz Saidane, L. (2012). Performance evaluation of the earliest deadline first policy over ad hoc networks. International Journal of Ad Hoc and Ubiquitous Computing, 10(3), 175–195.CrossRefGoogle Scholar
  10. 10.
    Kumrawat, M., & Dhawan, M. (2014). Survey on energy efficient approach for wireless multimedia sensor network IJCSIT). International Journal of Computer Science and Information Technologies, 5(4), 5517–5520.Google Scholar
  11. 11.
    Jo, S. K., Ikram, M., Jung, I., Ryu, W., & Kim, J. (2014). Power efficient clustering for wireless multimedia sensor network. International Journal of Distributed Sensor Networks, 10, 148595.CrossRefGoogle Scholar
  12. 12.
    Han, G., Jiang, J., Guizani, M., & Rodrigues, J. J. P. C. (2016). Green routing protocols for wireless multimedia sensor networks. IEEE Wireless Communications, 23(6), 140–146.CrossRefGoogle Scholar
  13. 13.
    Phan, K. T., Fan, R., Jiang, H., Vorobyov, S. A., & Tellambura, C. (2009). Network lifetime maximization with node admission in wireless multimedia sensor networks. IEEE Transactions on Vehicular Technology, 58(7), 3640–3646.CrossRefGoogle Scholar
  14. 14.
    Ukani, V., Kothari, A., & Zaveri, T. (2014). An energy efficient routing protocol for wireless multimedia sensor network. In International conference on devices, circuits and communications (ICDCCom) (pp 1–6). IEEE.Google Scholar
  15. 15.
    Bennis, I., Zytoune, O., Aboutajdine, D., & Fouchal, H. (2013). Low energy geographical routing protocol for wireless multimedia sensor networks. In 9th International wireless communications and mobile computing conference (IWCMC). IEEE.Google Scholar
  16. 16.
    Abd El Kader, M. E. E. D., Youssif, A. A. A., Ghalwash, A. Z., et al. (2016). Energy aware and adaptive cross-layer scheme for video transmission over wireless sensor networks. IEEE Sensors Journal, 16(21), 7792–7802.CrossRefGoogle Scholar
  17. 17.
    Nayyar, A., Bashir, F., et al. (2011). Load based energy aware multimedia routing protocol-(lear). In 3rd International conference on computer research and development (ICCRD) (Vol. 2, pp. 427–430). IEEE.Google Scholar
  18. 18.
    Shahzad, A., Shah, G. A, & Khattak, A. U. (2011). QoS-supported energy-efficient MAC (QEMAC) protocol based on IEEE 802.11 e for wireless multimedia sensor networks. In 5th International conference on new trends in information science and service science (NISS) (Vol. 1, pp. 200–204). IEEE.Google Scholar
  19. 19.
    Shah, G. A., Liang, W., & Akan, O. B. (2012). Cross-layer framework for QoS support in wireless multimedia sensor networks. IEEE Transactions on Multimedia, 14(5), 1442–1455.CrossRefGoogle Scholar
  20. 20.
    Zhang, F., Todd, T. D., Zhao, D., & Kezys, V. (2004). Power saving access points for IEEE 802-11 wireless network infrastructure. Wireless Communications and Networking Conference (WCNC), 1, 195–200.Google Scholar
  21. 21.
    Zefreh, M. S., & Todd, T. D. (2014). Energy provisioning in green mesh networks using positional awareness. IEEE Transactions on Vehicular Technology, 63(8), 4064–4076.CrossRefGoogle Scholar
  22. 22.
    Gatzianas, M., Georgiadis, L., & Tassiulas, L. (2010). Control of wireless networks with rechargeable batteries (transactions papers). IEEE Transactions on Wireless Communications, 9(2), 581–593.CrossRefGoogle Scholar
  23. 23.
    Voigt, T., Ritter, H., & Schiller, J. (2003). Utilizing solar power in wireless sensor networks. In Proceedings of 28th annual IEEE international conference on local computer networks, LCN’03 (pp. 416–422). IEEE.Google Scholar
  24. 24.
    Abbas, M. M., Tawhid, M. A., Saleem, K., Muhammad, Z., Saqib, N. A., Malik, H., et al. (2014). Solar energy harvesting and management in wireless sensor networks. International Journal of Distributed Sensor Networks, 10(7), 436107.CrossRefGoogle Scholar
  25. 25.
    Kosunalp, S., & Cihan, A. (2017). Harvesting solar energy for limited-energy problem in wireless sensor networks. In 25th Signal processing and communications applications conference (SIU) (pp. 1–4). IEEE.Google Scholar
  26. 26.
    Chen, S., & Muntean, G. M. (2012). E-mesh: An energy-efficient cross-layer solution for video delivery in wireless mesh networks. In Shengyang (pp. 1–7). IEEE.Google Scholar
  27. 27.
    Fafoutis, X., Di Mauro, A., Orfanidis, C., & Dragoni, N. (2015). Energy-efficient medium access control for energy harvesting communications. IEEE Transactions on Consumer Electronics, 61(4), 402–410.CrossRefGoogle Scholar
  28. 28.
    Bui, N., & Rossi, M. (2015). Staying alive: System design for self-sufficient sensor networks. ACM Transactions on Sensor Networks (TOSN), 11(3), 40.CrossRefGoogle Scholar
  29. 29.
    Romaniello, G., Alphand, O., Guizzetti, R., & Duda, A. (2015). Sustainable traffic aware duty-cycle adaptation in harvested multi-hop wireless sensor networks. In IEEE 81st Vehicular technology conference (VTC Spring) (pp. 1–6). IEEE.Google Scholar
  30. 30.
    Kansal, A., Hsu, J., Zahedi, S., & Srivastava, M. B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 6(4), 32.CrossRefGoogle Scholar
  31. 31.
    Vigorito, C. M., Ganesan, D., & Barto, A. G. (2007). Adaptive control of duty cycling in energy-harvesting wireless sensor networks. In 4th Annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks, SECON’07 (pp. 21–30). IEEE.Google Scholar
  32. 32.
    Buchli, B., Sutton, F., Beutel, J., & Thiele, L. (2014). Dynamic power management for long-term energy neutral operation of solar energy harvesting systems. In Proceedings of the 12th ACM conference on embedded network sensor systems (pp. 31–45). ACM.Google Scholar
  33. 33.
    Peng, S., & Low, C. P. (2014). Prediction free energy neutral power management for energy harvesting wireless sensor nodes. Ad Hoc Networks, 13, 351–367.CrossRefGoogle Scholar
  34. 34.
    Peng, S., Wang, T., & Low, C. P. (2015). Energy neutral clustering for energy harvesting wireless sensors networks. Ad Hoc Networks, 28, 1–16.CrossRefGoogle Scholar
  35. 35.
    Peng, S., & Low, C. P. (2015). Energy neutral directed diffusion for energy harvesting wireless sensor networks. Computer Communications, 63, 40–52.CrossRefGoogle Scholar
  36. 36.
    Teng, R., Li, H.-B., Zhang, B., & Miura, R. (2016). Differentiation presentation for sustaining internet access in a disaster-resilient homogeneous wireless infrastructure. IEEE Access, 4, 514–528.CrossRefGoogle Scholar
  37. 37.
    Heusse, M., Rousseau, F., Berger-Sabbatel, G., & Duda, A. (2003). Performance anomaly of 802.11b. In 22th Annual joint conference of the IEEE computer and communications societies (INFOCOM) (Vol. 2, pp. 836–843).Google Scholar
  38. 38.
    IEEE Standards Association et al. (2012). 802.11-2012-IEEE standard for information technology–telecommunications and information exchange between systems local and metropolitan area networks–specific requirements part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications. IEEE Standard.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer EngineeringIran University of Science and TechnologyTehranIran

Personalised recommendations