自适应模糊逻辑方案改进车载自组织网络性能

Improving VANET Performance Based on Heuristic and Adaptive Fuzzy Logic Scheme

为了确保车载自组织网络(VANET)数据包的有效传输,VANET中的节点应能适应VANET拓扑结构的变化。现有的VANET方案只从一个参数优化竞争窗尺寸和传输功率,未考虑干扰这一主要因素在VANET劣化传输时的影响。在VANET运行的时间内,干扰或数据丢包可以出现在不同的传输阶段,改进启发式和自适应模糊逻辑方案(Ha FL),基于碰撞丢包率、信噪比(SINR)及队列溢出3个参数,模糊逻辑自适应地优化数据包竞争窗尺寸。Ha FL仿真结果表明,与现有方案比较,Ha FL能提高吞吐量,降低端到端延迟和提高数据包传输的成功率。

In order to ensure VANET package transmission effectively, nodes in VANET should react adaptively to topology change in VANET. The current existing schemes in VANET only utilize a single parameter to optimize the contention window and transmission power without consideration on the effects of interference that is as one of the main factors in VANET transmission degradation. In VANET, package loss can occur at different stages of transmission due to interference or elapsed time. In the proposed Ha FL, fuzzy logic is used to adaptively optimize the contention window size based on three parameters namely collision rate, SINR and queue overflow. Simulation results show that Ha FL demonstrates adaptability using improved throughput, lowers end-to-end delay and improves package success rate in comparison with the existing schemes.