DOI QR코드

DOI QR Code

Stochastic Mobility Model Design in Mobile WSN

WSN 노드 이동 환경에서 stochastic 모델 설계

  • Yun, Dai Yeol (Department of Information and Communication Engineering, IIT, Kwangwoon University) ;
  • Yoon, Chang-Pyo (Department Of Computer & Mobile Convergence, GyeongGi University of Science and Technology) ;
  • Hwang, Chi-Gon (Department of Computer Engineering, IIT, Kwangwoon University)
  • Received : 2021.06.30
  • Accepted : 2021.07.16
  • Published : 2021.08.31

Abstract

In MANET(mobile ad hoc network), Mobility models vary according to the application-specific goals. The most widely used Random WayPoint Mobility Model(RWPMM) is advantageous because it is simple and easy to implement, but the random characteristic of nodes' movement is not enough to express the mobile characteristics of the entire sensor nodes' movements. The random mobility model is insufficient to express the inherent movement characteristics of the entire sensor nodes' movements. In the proposed Stochastic mobility model, To express the overall nodes movement characteristics of the network, the moving nodes are treated as random variables having a specific probability distribution characteristic. The proposed Stochastic mobility model is more stable and energy-efficient than the existing random mobility model applies to the routing protocol to ensure improved performances in terms of energy efficiency.

노드 이동 모델은 활용 서비스 및 목적에 따라 제안되어야 한다. 현재 가장 널리 활용되는 무작위 이동 모델은 간편하고 구현하기가 쉽다는 장점이 있다. 이 모델에서 노드 이동 특성은 이동 속도와 이동 방향을 무작위 속성으로 처리하며, 매번 노드들의 이동이 서로 독립적으로 발생한다. 본 논문에서는 모바일 애드혹 네트워크 이동 환경에서 적용 가능한 확률론적인 이동 모델을 제안한다. 제안 확률 이동 모델에서는 네트워크의 전체 노드 이동 특성을 표현하기 위하여 이동하는 노드 수와 노드 이동 거리가 특정 확률 분포 특성을 가지도록 랜덤 변수로 처리한다. 또한, 제안 이동 모델을 대표적인 무작위 이동 모델과 비교하여 노드들의 이동 변화에 안정적인 특성을 나타냄을 보이고, 기존 라우팅 프로토콜에 제안 모델을 적용하여 에너지 소비 효율 측면에서 향상된 특성을 보임을 확인한다.

Keywords

References

  1. W. Dargie and C. Poellabauer, Fundamentals of wireless sensor networks: theory and practice, John Wiley & Sons, NY, 2010.
  2. M. Shreshtha and R. Kumar, "A literature survey on various clustering approaches in wireless sensor network," 2016 2nd international conference on communication control and intelligent systems, pp. 18-22, 2016.
  3. J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, "System architecture directions for networked sensors," ACM Sigplan notices, vol. 35, no. 11, pp. 93-104, 2000. https://doi.org/10.1145/356989.356998
  4. M. Appiah, "Performance comparison of mobility models in Mobile Ad Hoc Network (MANET)," in 2017 1st International Conference on Next Generation Computing Applications (NextComp), pp. 47-53, 2017.
  5. T. Alam, "Fuzzy Control Based Mobility Framework for Evaluating Mobility Models in MANET of Smart Devices," ARPN Journal of Engineering and Applied Sciences, vol. 12, no. 15, pp. 4526-4538, 2017.
  6. A. Pullin, C. Pattinson, and A. L. Kor, "Building Realistic Mobility Models for Mobile Ad Hoc Networks," in Informatics. Multidisciplinary Digital Publishing Institute, vol. 5, no. 2, pp. 22, 2018. https://doi.org/10.3390/informatics5020022
  7. T. Camp, J. Boleng, and V. Davies, "A survey of mobility models for ad hoc network research," Wireless communications and mobile computing, vol. 2, no. 5, pp. 483-502, 2002. https://doi.org/10.1002/wcm.72
  8. W. Wang, J. Wang, M. Wang, B. Wang, and W. Zhang, "A realistic mobility model with irregular obstacle constraints for mobile ad hoc networks," Wireless Networks, vol. 25, no. 2, pp. 487-506, 2019. https://doi.org/10.1007/s11276-017-1569-z
  9. B. Divecha, A. Abraham, C. Grosan, and S. Sanyal, "Impact of Node Mobility on MANET Routing Protocols Models," Journal of Digital Information Management, vol. 5, no. 1, pp. 19-24, 2007.
  10. S. C. Gupta and V. K. Kapoor, Fundamentals of mathematical statistics, Sultan Chand & Sons, 2020.
  11. J. Zhang and R. Yan, "Centralized energy-efficient clustering routing protocol for mobile nodes in wireless sensor networks," IEEE Communications Letters, vol. 23, no. 7, pp. 1215-1218, 2019. https://doi.org/10.1109/lcomm.2019.2917193