Adaptive Routing Design for Flying Ad Hoc Networks: A Joint Prediction Approach

Min Zhang, Hao Cheng, Peng Yang, Chao Dong, Haitao Zhao, Qihui Wu, Tony Q.S. Quek

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Flying Ad Hoc Networks (FANETs) are essential for a wide range of military and civil applications as they significantly reduce mission duration and improve coverage compared to using a single Unmanned Aerial Vehicle (UAV). Nevertheless, the dynamic and mobile nature of FANETs, coupled with fluctuating data traffic patterns, pose significant challenges for adaptive routing and efficient packet delivery. At present, most of the existing routing protocols for FANETs are designed based on mobility or topology information without taking into account data traffic and the associated joint decision-making approach. This narrow focus can result in poor network performance, characterized by longer delivery delay and lower delivery ratio. Thus, this paper proposes the Joint Prediction and Entropy weight-based (JPE) routing protocol by considering both current and future network conditions. The protocol uses a Long Short-Term Memory (LSTM) model to predict and obtain the mobility, buffer available size, and Link Expiration Time (LET) of each Neighbouring UAV (NU) in order to avoid high-mobility, high-traffic, and weak-link UAVs and establish an appropriate path. The routing decision problem is then formulated as an optimization problem and solved using the proposed Entropy Weight-based Multi-Metric (EWMM) approach. The integrated prediction and decision process considers both current and future multi-metric factors. Simulation results demonstrate the effectiveness of the LSTM-based Joint Prediction (JP) model and show that the JPE protocol outperforms the PAP and SPA protocols, improving Packet Delivery Ratio (PDR) and delay performance by 30.13% and 31.24% respectively.

Original languageEnglish
Pages (from-to)2593-2604
Number of pages12
JournalIEEE Transactions on Vehicular Technology
Volume73
Issue number2
DOIs
Publication statusPublished - 2024 Feb 1

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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