Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Evaluation of simulator tools and power-aware scheduling model for wireless sensor networks

The sharp increase of the wireless sensor networks (WSNs) performance has increased their power requirements. However, with a limited battery lifetime it is more and more difficult to deploy many more sensors with today's solutions. Therefore, the authors need to implement autonomous WSNs without any human intervention or external power supply. To this end, this study proposes an effective strategy to ensure an energy consumption gain that takes into account time constraints through a power-aware model based on the dynamic voltage and frequency scaling and the dynamic power management that are appropriate to the WSNs and on a global Earliest Deadline First scheduler. To select the most suitable simulator to integrate and simulate the developed models, >25 of the existing WSN simulators are outlined and evaluated. On the basis of this comparative study analysis, the authors chose the simulation tool for real-time multiprocessor scheduling (STORM) to validate their work for its multiple advantages.

References

    1. 1)
      • 29. Dhurandher, S.K., Misra, S., Obaidat, M.S., et al: ‘Uwsim: a simulator for underwater sensor networks’, Simulation, 2008, 84, (7), pp. 327338.
    2. 2)
      • 46. Srinivasan, A., Baruah, S.: ‘Deadline-based scheduling of periodic task systems on multiprocessors’, Inf. Process. Lett., 2002, 84, (2), pp. 9398.
    3. 3)
      • 25. Liu, J., Liu, X., Lee, E.A.: ‘Modeling distributed hybrid systems in Ptolemy II’. Proc. of the American Control Conf., 2001, vol. 6, pp. 49844985.
    4. 4)
      • 19. Titzer, B.L., Lee, D.K., Palsberg, J.: ‘Avrora: scalable sensor network simulation with precise timing’. Fourth Int. Symp. on Information Processing in Sensor Networks, 2005, pp. 477482.
    5. 5)
      • 10. Obeid, A.M., Karray, F., Jmal, M.W., et al: ‘Towards realisation of wireless sensor network-based water pipeline monitoring systems: a comprehensive review of techniques and platforms’, IET Sci. Meas. Technol., 2016, 10, (5), pp. 420426.
    6. 6)
      • 38. Du, W., Mieyeville, F., Navarro, D., et al: ‘Idea1: a validated SystemC-based system-level design and simulation environment for wireless sensor networks’, EURASIP J. Wirel. Commun. Netw., 2011, (1), pp. 120.
    7. 7)
      • 32. Hammoodi, I., Stewart, B., Kocian, A., et al: ‘A comprehensive performance study of Opnet modeler for Zigbee wireless sensor networks’. Third Int. Conf. Next Generation Mobile Applications, Services and Technologies, 2009, pp. 357362.
    8. 8)
      • 53. Kansal, A., Hsu, J., Zahedi, S., et al: ‘Power management in energy harvesting sensor networks’, ACM Trans. Embed. Comput. Syst. (TECS), 2007, 6, (4), p. 32.
    9. 9)
      • 23. Issariyakul, T., Hossain, E.: ‘An introduction to network simulator NS2’ (Springer, 2012).
    10. 10)
      • 11. Rawat, P., Singh, K., Chaouchi, H., et al: ‘Wireless sensor networks: a survey on recent developments and potential synergies’, J. Supercomput., 2014, 68, (1), pp. 148.
    11. 11)
      • 5. Varghese, B., John, N.E., Sreelal, S., et al: ‘Design and development of an RF energy harvesting wireless sensor node (EH-WSN) for aerospace applications’, Procedia Comput. Sci., 2016, 93, pp. 230237.
    12. 12)
      • 51. Dargie, W.: ‘Dynamic power management in wireless sensor networks: state-of-the-art’, IEEE Sens. J., 2012, 12, (5), pp. 15181528.
    13. 13)
      • 20. Osterlind, F., Dunkels, A., Eriksson, J., et al: ‘Cross-level sensor network simulation with COOJA’. 31st IEEE Conf. on Local Computer Networks, 2006, pp. 641648.
    14. 14)
      • 49. Hoang, V.T., Julien, N., Berruet, P.: ‘Increasing the autonomy of wireless sensor node by effective use of both DPM and DVFS methods’, ‘Faible tension faible consommation (FTFC)’ (IEEE, 2013), pp. 14.
    15. 15)
      • 40. Weber, D., Glaser, J., Mahlknecht, S.: ‘Discrete event simulation framework for power aware wireless sensor networks’. Fifth Int. Conf. on Industrial Informatics, 2007, vol. 1, pp. 335340.
    16. 16)
      • 1. Singh, S., Chand, S., Kumar, R., et al: ‘Neecp: Novel energy-efficient clustering protocol for prolonging lifetime of wsns’, IET Wireless Sensor Systems, 2016, 6, (5), pp. 151157.
    17. 17)
      • 4. Ojuroye, O., Torah, R., Beeby, S., et al: ‘Smart textiles for smart home control and enriching future wireless sensor network data’ (Springer, 2017), 22, pp. 159183.
    18. 18)
      • 42. Park, S., Savvides, A., Srivastava, M.B.: ‘Sensorsim: a simulation framework for sensor networks’. Proc. 3rd ACM Int. Workshop on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2000, pp. 104111.
    19. 19)
      • 15. Kulau, U., Rottmann, S., Schildt, S., et al: ‘Undervolting in real world WSN applications: a long-term study’. Int. Conf. on Distributed Computing in Sensor Systems (DCOSS), 2016, 2016, pp. 916.
    20. 20)
      • 21. Girod, L., Elson, J., Cerpa, A., et al: ‘Emstar: a software environment for developing and deploying wireless sensor networks’. Proc. of the General Track: USENIX Annual Technical Conf., 2004, pp. 283296.
    21. 21)
      • 36. Polley, J., Blazakis, D., McGee, J., et al: ‘Atemu: a fine-grained sensor network simulator’. First Annual IEEE Communications Society Conf. on Sensor and Ad Hoc Communications and Networks, 2004, pp. 145152.
    22. 22)
      • 41. Chen, G., Branch, J., Pflug, M., et al: ‘Sense: a wireless sensor network simulator’, ‘Advances in pervasive computing and networking’ (Springer, 2005), pp. 249267.
    23. 23)
      • 31. Varga, A., et al: ‘The OMNET++ discrete event simulation system’. Proc. European Simulation Multiconf. (ESM2001), 2001.
    24. 24)
      • 24. Chéour, R., Jmal, M., Lay-Ekuakille, A., et al: ‘Choice of efficient simulator tool for wireless sensor networks’. Int. Workshop on Measurements and Networking Proc. (M&N), Naples, Italy, 2013.
    25. 25)
      • 26. Nayyar, A., Singh, R.: ‘A comprehensive review of simulation tools for wireless sensor networks (WSNs)’, J. Wirel. Netw. Commun., 2015, 5, (1), pp. 1947.
    26. 26)
      • 14. Harkut, D., Ali, M., Lohiya, P.: ‘Scheduling task of wireless sensor network using earliest deadline first algorithm’, Int. J. Sci. Res. Comput. Sci. Eng., 2014, 2, (2), pp. 16.
    27. 27)
      • 6. Chéour, R., Jmal, M., Abid, M.: ‘Hybrid energy-efficient power management for wireless sensors networks’. Int. Conf. on Smart, Monitored and Controlled Cities (IEEE, Tunisia, 2017).
    28. 28)
      • 22. Chhimwal, M.P., Rai, D.S., Rawat, D.: ‘Comparison between different wireless sensor simulation tools’, IOSR J. Electron. Commun. Eng., 2013, 5, (2), pp. 5460.
    29. 29)
      • 34. Kroeller, A., Pfisterer, D., Buschmann, C., et al: ‘Shawn: a new approach to simulating wireless sensor networks’, arXiv preprint cs/0502003, 2005.
    30. 30)
      • 50. Popovici, E., Magno, M., Marinkovic, S.: ‘Power management techniques for wireless sensor networks: a review’. Fifth IEEE Int. Workshop on Advances in Sensors and Interfaces (IWASI), 2013, pp. 194198.
    31. 31)
      • 47. Chen, G., Huang, K., Knoll, A.: ‘Energy optimization for real-time multiprocessor system-on-chip with optimal DVFS and DPM combination’, ACM Trans. Embed. Comput. Syst. (TECS), 2014, 13, (3s), p. 111.
    32. 32)
      • 17. Helkey, J., Holder, L., Shirazi, B.: ‘Comparison of simulators for assessing the ability to sustain wireless sensor networks using dynamic network reconfiguration’, Sust. Comput. Inf. Syst., 2016, 9, pp. 17.
    33. 33)
      • 48. Liu, S., Qiu, Q., Wu, Q.: ‘Energy aware dynamic voltage and frequency selection for real-time systems with energy harvesting’, ‘Design, automation and test in Europe’ (IEEE, 2008), pp. 236241.
    34. 34)
      • 9. Bartariya, S., Rastogi, A.: ‘Security in wireless sensor networks: Attacks and solutions’, Environment, 2016, 5, (3), pp. 214220.
    35. 35)
      • 2. Benhaddou, D., Al-Fuqaha, A.: ‘Wireless sensor and mobile ad-hoc networks: vehicular and space applications’ (Springer, 2015).
    36. 36)
      • 44. Sobeih, A., Hou, J.C., Kung, L.-C., et al: ‘J-sim: a simulation and emulation environment for wireless sensor networks’, Wirel. Commun., 2006, 13, (4), pp. 104119.
    37. 37)
      • 35. Landsiedel, O., Wehrle, K., Götz, S.: ‘Accurate prediction of power consumption in sensor networks’. Proc. Second Workshop on Embedded Networked Sensors, 2005.
    38. 38)
      • 28. Shnayder, V., Hempstead, M., Chen, B., et al: ‘Simulating the power consumption of large-scale sensor network applications’. Proc. 2nd Int. Conf. on Embedded Networked Sensor Systems, 2004, pp. 188200.
    39. 39)
      • 52. Brihi, A.: ‘Investigation into the dependency between resource utilization, power consumption and performance in multimedia servers’. PhD thesis, MSc dissertation, Department of Computer Science, Technische Universitat Dresden, 2012.
    40. 40)
      • 3. Khriji, S., El Houssaini, D., Jmal, M.W., et al: ‘Precision irrigation based on wireless sensor network’, IET Sci. Meas. Technol., 2014, 8, (3), pp. 98106.
    41. 41)
      • 43. IRCCYN: ‘Présentation de storm’, 2015, http://storm.rts-software.org/doku.php?id=start=.
    42. 42)
      • 55. Le, T.N.: ‘Global power management system for self-powered autonomous wireless sensor node’. PhD thesis, Université Rennes 1, 2014.
    43. 43)
      • 7. Guru, R.: ‘Energy efficiency mechanisms in wireless sensor networks: a survey’, Int. J. Comput. Appl., 2016, 139, (14), pp. 2733.
    44. 44)
      • 45. Goossens, J.: ‘Scheduling of offset free systems’, Real-Time Syst., 2003, 24, (2), pp. 239258, Available at: http://dx.doi.org/10.1023/A:1021782503695.
    45. 45)
      • 18. Lattanzi, E., Freschi, V., Dromedari, M., et al: ‘A fast and accurate energy source emulator for wireless sensor networks’, EURASIP J. Embed. Syst., 2017, 2016, (1), p. 18.
    46. 46)
      • 37. Nasir, A., Soong, B.-H.: ‘Energysim a novel, fast, extensible wireless sensor network mac protocol simulator for evaluating energy efficiency’. Eighth Int. Conf. Information, Communications and Signal Processing (ICICS), 2011, pp. 15.
    47. 47)
      • 27. Korkalainen, M., Sallinen, M., Karkkainen, N., et al: ‘Survey of wireless sensor networks simulation tools for demanding applications’. Fifth Int. Conf. on Networking and Services, 2009, pp. 102106.
    48. 48)
      • 33. Levis, P., Lee, N., Welsh, M., et al: ‘Tossim: accurate and scalable simulation of entire Tinyos applications’. Proc. First Int. Conf. on Embedded Networked Sensor Systems, 2003, pp. 126137.
    49. 49)
      • 13. Sankar Ramachandran, G., Daniels, W., Matthys, N., et al: ‘Measuring and modeling the energy cost of reconfiguration in sensor networks’, IEEE Sens. J., 2015, 15, (6), pp. 33813389.
    50. 50)
      • 8. Shaikh, F.K., Zeadally, S.: ‘Energy harvesting in wireless sensor networks: a comprehensive review’, Renew. Sustain. Energy Rev., 2016, 55, pp. 10411054.
    51. 51)
      • 12. Lamonaca, F., Gasparri, A., Garone, E., et al: ‘Clock synchronization in wireless sensor network with selective convergence rate for event driven measurement applications’, IEEE Trans. Instrum. Meas., 2014, 63, (9), pp. 22792287.
    52. 52)
      • 54. Zhu, N.: ‘Simulation and optimization of energy consumption in wireless sensor networks’. PhD thesis, Ecole centrale de Lyon, Ecully, 2013.
    53. 53)
      • 16. Dhall, S.K., Liu, C.L.: ‘On a real-time scheduling problem’, Oper. Res., 1978, 26, (1), pp. 127140.
    54. 54)
      • 30. Boulis, A.: ‘Castalia, a simulator for wireless sensor networks and body area networks, version 2.2’, User's manual (NICTA, 2009).
    55. 55)
      • 39. Fahmy, H.M.A.: ‘Simulators and emulators for WSNs’, ‘Wireless sensor networks’ (Springer, 2016), pp. 381491.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cdt.2017.0003
Loading

Related content

content/journals/10.1049/iet-cdt.2017.0003
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address