• DocumentCode
    2221571
  • Title

    A Modified Discrete Differential Evolution based TDMA scheduling scheme for many to one communications in wireless sensor networks

  • Author

    Islam, Sk Minhazul ; Ghosh, Saurav ; Das, Swagatam ; Abraham, Ajith ; Roy, Subhrajit

  • Author_Institution
    Dept. of Electron. & Telecommun. Eng., Jadavpur Univ., Kolkata, India
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    1950
  • Lastpage
    1957
  • Abstract
    Time Division Multiple Access (TDMA) plays an important role in MAC (Medium Access Control) for wireless sensor networks providing real-time guarantees and potentially reducing the delay and also it saves power by eliminating collisions. In TDMA based MAC, the sensor are not allowed to radiate signals when they are not engaged. On the other hand, if there are too many switching between active and sleep modes it will also unnecessary waste energy. In this paper, we have presented a multi-objective TDMA scheduling problem that has been demonstrated to prevent the wasting of energy discussed above and also further improve the time performance. A Modified Discrete Differential Evolution (MDDE) algorithm has been proposed to enhance the converging process in the proposed effective optimization framework. Simulation results are given with different network sizes. The results are compared with the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) and the original Discrete DE algorithm (DDE). The proposed MDDE algorithm has successfully outperformed these three algorithms on the objective specified, which is the total time or energy for data collection.
  • Keywords
    genetic algorithms; particle swarm optimisation; scheduling; time division multiple access; wireless sensor networks; MDDE algorithm; energy wasting; genetic algorithm; many to one communication; medium access control; modified discrete differential evolution algorithm; multiobjective TDMA scheduling problem; optimization framework; original Discrete DE algorithm; particle swarm optimization; real-time guarantee; sleep mode; time division multiple access; wireless sensor network; Encoding; Frequency modulation; Genetic algorithms; Optimization; Scheduling; Time division multiple access; Wireless sensor networks; Differential Evolution; Genetic algorithm; Particle swarm optimization; TDMA scheduling; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949854
  • Filename
    5949854