Battery-Aware Systems

  • Ajit PalEmail author


With the proliferation of portable battery-operated devices, smaller, lighter, more powerful, and longer-lasting battery is a much sought-after commodity. Powering laptops, handhelds, cell phones, pagers, watches, medical devices, and many other modern gadgets, batteries play a crucial role in supporting today’s cutting-edge technologies. The widening gap between the increasing power consumption and power density of the popular battery technologies is highlighted to emphasize the relevance of battery-aware systems. Battery-aware synthesis approaches try to make efficient use of the available energy in the battery. So optimization of the battery lifetime, i.e., performing maximum amount of computation per recharge of battery, is one of the primary objectives for portable computing system design. An overview of commonly used battery technologies is provided, and the characteristics of a rechargeable battery are specified. The underlying process of battery discharge is explained. Realizations of battery-driven systems including battery-aware sensor network are presented.


Assisted-LEACH Battery-aware task scheduling Battery discharge characteristics Battery gap Battery technologies Energy-aware routing Energy density LEACH Lithium ion Lithium polymer Memory effect Nickel cadmium Nickel–metal hydride Rate capacity effect Rechargeable alkaline Recovery effect 


  1. 1.
    Lahiri, K., Raghunathan, A., Dey, S., Panigrahi, P.: Battery-driven system design: A new frontier in low power design. In: Proceedings of the 15th International Conference on VLSI Design 2002, pp. 261–267, Bangalore, January 2002Google Scholar
  2. 2.
    O’Hara, T., Wesselmark, M.: Battery technologies: A general overview & focus on Lithium-Ion, IntertekGoogle Scholar
  3. 3.
    Linden, D., Reddy, T.B.: Handbook of Batteries, 3rd edn. McGraw-Hill (2002)Google Scholar
  4. 4.
    Rakhmatov, D., Vradhula, S.: Energy measurement for battery-powered embedded systems. ACM Trans. Embed. Comput. Syst. 2(2), 277–324 (2003)Google Scholar
  5. 5.
    Rakhmatov, D., Vrudhula, S., Chakrabarti, C.: Battery-conscious task sequencing for portable devices including voltage/clock scaling. In: Proceedings of the 39th conference on Design automation (DAC 2002), pp. 189–194, 10–14 June 2002Google Scholar
  6. 6.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE 40(8), 102–114 (2002)Google Scholar
  7. 7.
    Sravan, A., Kundu, S., Pal, A.: Low power sensor node for a wireless sensor network. In: Proceedings of the 20th International Conference on VLSI 2007, pp. 445–450, Bangalore, January 2007Google Scholar
  8. 8.
    Akkaya, K., Mohamed Younis, M.: A survey on routing protocols for wireless sensor networks. Ad Hoc Netw. 3(3), 325–349 (2005)CrossRefGoogle Scholar
  9. 9.
    Pantazis, N.A., Nikolidakis, S.A., Vergados, D.D.: Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Commun. Surv. Tutor. 15(2), 551–591 (2013)Google Scholar
  10. 10.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: IEEE Computer Society Proceedings of the Thirty Third Hawaii International Conference on System Sciences (HICSS ’00), vol. 8, pp. 8020, Washington, DC, USA, January 2000Google Scholar
  11. 11.
    Singh, S.K., Singh, M.P., Singh, D.K.: Routing protocols in wireless sensor networks—A survey. Proc. Int. J. Comput. Sci. Eng. Surv. (IJCSES) 1(2), 63–83 (2010)CrossRefGoogle Scholar
  12. 12.
    Chowdhury, P., Chakrabarti, C.: Static task-scheduling algorithms for battery-powered DVS systems. IEEE Trans. Very Larg. Scale Integr. (VLSI) Syst. 13(2) 226–237 (2005)Google Scholar
  13. 13.
    Kumar, S.V., Pal, A.: Assisted-Leach (A-Leach): Energy efficient routing protocol for wireless sensor networks. Int. J. Comput. Commun. Eng. 2(4), 420–424 (2013)CrossRefGoogle Scholar
  14. 14.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wirel. Commun. 1(4), 660–670 (2002)CrossRefGoogle Scholar
  15. 15.
    Intagagonwiwat, C., Govindan, R., Estrin, D.: Directed diffusion: A scalable and robust communication paradigm for sensor networks. In: Proceedings of the Mobicom’00, pp. 56–67, Boston (2000)Google Scholar
  16. 16.
    Martin, S.M., Flautner, K., Mudge, T., Blaauw, D.: Combined dynamic voltage scaling and adaptive body biasing for lower power microprocessors under dynamic workloads. IEEE/ACM International Conference on In Computer Aided Design, 2002(ICCAD 2002), pp. 721–725, (2002)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia

Personalised recommendations