MPR Node Selection Improvement in OLSR Based on Binary Cuckoo Search

Unmanned aerial vehicle (UAV) relay is an appropriate choice for emergency communications because of its good mobility and flexibility of placement. In this paper, the optimized link state routing (OLSR) based on binary cuckoo search (BCS) is proposed to improve the Multi-Point Relay (MPR) node selection efficiency and survival time of UAV relay network. The traditional OLSR uses the greedy algorithm to select the MPR set, ignoring the key factors such as node energy in the emergency communication relay scenario. In the optimization process, it is easy to fall into local optimal and generate redundancy, increasing protocol overhead and network delay. Therefore, binary Cuckoo search with energy sensing strategy are adopted to solve MPR node selection which is the discrete optimization problem by randomly finding the optimal solution through Lévy flight. The NS3 network simulator is used to simulate our proposed model. The results show that the improved OLSR based on the BCS has better MPR node search efficiency and higher energy utilization rate of nodes, which can effectively solve the survival time problem of emergency communication networks.