Flowlet-based Stateful Multipath Forwarding in Heterogeneous Internet of Things

Concurrent multipath transfer effectively improves network throughput and reliability by utilizing the unoccupied network links. However, the performance of concurrent multipath transfer degrades significantly in the heterogeneous Internet of Things. The reason is that the disorder and retransmission will increase sharply if the quality of links are greatly different. This paper proposes a multipath stateful forwarding mechanism in the granularity of flowlet, which is featured with planning the flowlet forwarding dynamically to improve the transmission success rate. Besides, our mechanism implements stateful forwarding by improving the state information processing capability of the data plane. It can adjust the size of the flowlet based on the network performance of the path, thereby improving the bandwidth resource utilization of the system. In particular, the proposed mechanism can sense network congestion status dynamically, detect network anomalies, and re-plan the forwarding strategy. Experimental results show that in the harsh environment (link quality varies greatly among the three test paths), the proposed mechanism can improve the throughput by 114.7% and reduce the percentage of out of order packets by 29.5% compared with the Round-Robin Scheduling mechanism.