AntHocNet: an adaptive nature‐inspired algorithm for routing in mobile ad hoc networks. In this paper, we describe AntHocNet, an algorithm for routing in mobile ad hoc networks. It is a hybrid algorithm, which combines reactive path setup with proactive path probing, maintenance and improvement. The algorithm is based on the nature‐inspired ant colony optimisation framework. Paths are learned by guided Monte Carlo sampling using ant‐like agents communicating in a stigmergic way. In an extensive set of simulation experiments, we compare AntHocNet with AODV, a reference algorithm in the field. We show that our algorithm can outperform AODV on different evaluation criteria. AntHocNet’s performance advantage is visible over a broad range of possible network scenarios, and increases for larger, sparser and more mobile networks.

References in zbMATH (referenced in 15 articles )

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  1. Karthikeyan, P.; Baskar, S.: Genetic algorithm with ensemble of immigrant strategies for multicast routing in ad hoc networks (2015) ioport
  2. Vallikannu, R.; George, A.; Srivatsa, S. K.: Autonomous localization based energy saving mechanism in indoor MANETs using ACO (2015)
  3. Cañas, Delfín Rupérez; Villalba, Luis Javier García; Orozco, Ana Lucila Sandoval; Kim, Tai-Hoon: Adaptive routing protocol for mobile ad hoc networks (2014)
  4. Kambayashi, Yasushi: A review of routing protocols based on ant-like mobile agents (2013)
  5. Karthikeyan, P.; Baskar, S.; Alphones, A.: Improved genetic algorithm using different genetic operator combinations (GOCs) for multicast routing in ad hoc networks (2013) ioport
  6. Gorodetskii, V. I.: Self-organization and multiagent systems. I: Models of multiagent self-organization (2012)
  7. Saleem, Muhammad; Ullah, Israr; Farooq, Muddassar: \textitBeeSensor: an energy-efficient and scalable routing protocol for wireless sensor networks (2012) ioport
  8. Saleem, Muhammad; Di Caro, Gianni A.; Farooq, Muddassar: Swarm intelligence based routing protocol for wireless sensor networks: survey and future directions (2011) ioport
  9. Labella, Thomas Halva; Dietrich, Isabel; Dressler, Falko: Hybrid simulation of sensor and actor networks with BARAKA (2010) ioport
  10. Oommen, B. John; Misra, Sudip: Fault-tolerant routing in adversarial mobile ad hoc networks: an efficient route estimation scheme for non-stationary environments (2010) ioport
  11. Kolavali, Sudha Rani; Bhatnagar, Shalabh: Ant colony optimization algorithms for shortest path problems (2009)
  12. Shuang, Bing; Li, Zhenbo; Chen, Jiapin: An ant-based on-demand energy route protocol for IEEE 802.15.4 mesh network (2009) ioport
  13. Mirabedini, Seyed Javad; Teshnehlab, Mohammad; Shenasa, M. H.; Movaghar, Ali; Rahmani, Amir Masoud: AFAR: adaptive fuzzy ant-based routing for communication networks (2008)
  14. Blesa, Maria J.; Blum, Christian: Finding edge-disjoint paths in networks: an ant colony optimization algorithm (2007)
  15. Soltani, Azadeh; Akbarzadeh-T, M.-R.; Naghibzadeh, M.: Helping ants for adaptive network routing (2006)