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Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks

Author

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  • Guangzhi Han
  • Haifeng Jiang
  • Liansheng Lu
  • Shanshan Ma
  • Shuo Xiao

Abstract

Hybrid wireless mesh networks are suitable for complex environment communication in coal mine. Mesh clients with application service and routing function in hybrid wireless mesh networks can form a highly robust hybrid network with mesh routers. The processes of nutrient flux transfer and path choice in Physarum network are similar to data transmission and routing selection in hybrid wireless mesh networks. In this article, we use Physarum-inspired autonomic optimization model to design a Physarum-inspired multi-parameter adaptive routing protocol to improve the service quality of coal mine hybrid wireless mesh networks. Physarum-inspired multi-parameter adaptive routing protocol has achieved distributed routing decision by drawing the hybrid wireless mesh network parameters into Poisson’s equation of Physarum-inspired autonomic optimization model to measure the quality of link and implements two adjustment strategies to make the protocol more adaptive. The resource-dependent adjustment, which considers the irreversible energy consumption and recoverable buffer occupation, makes the energy consumption problem prominent when there is a lack of energy. The position-dependent adjustment makes routing decision efficient according to the load of different positions, which is caused by many-to-one data transmission model in coal mine. Based on NS2, simulation experiments are performed to evaluate the performance of Physarum-inspired multi-parameter adaptive routing protocol, and the results are compared with those of ad hoc on-demand distance vector, HOPNET, ANT-DSR, and Physarum-inspired routing protocols. The experimental results show that the route path selected by Physarum-inspired multi-parameter adaptive routing protocol is better than those selected by the other four protocols in the performance of average end-to-end delay and delivery ratio. The balance of energy consumption and network load is achieved and the network lifetime is effectively prolonged when using Physarum-inspired multi-parameter adaptive routing protocol.

Suggested Citation

  • Guangzhi Han & Haifeng Jiang & Liansheng Lu & Shanshan Ma & Shuo Xiao, 2018. "Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:2:p:1550147718759217
    DOI: 10.1177/1550147718759217
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    1. Toshiyuki Nakagaki & Hiroyasu Yamada & Ágota Tóth, 2000. "Maze-solving by an amoeboid organism," Nature, Nature, vol. 407(6803), pages 470-470, September.
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