Design and implementation of an adaptive feedback queue algorithm over OpenFlow networks

The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Recently, several proposals for fulfilling the quality of service (QoS) guarantees have been presented. However, they can only support coarse-grained QoS with no guarantee of throughput, jitter, delay or loss rate for different applications. To address these more challenging problems, an adaptive scheduling algorithm for Parallel data Processing with Multiple Feedback (PPMF) queues based on software defined networks (SDN) is proposed in this paper, which can guarantee the quality of service of high priority traffic in multimedia applications. PPMF combines the queue bandwidth feedback mechanism to realise the automatic adjustment of the queue bandwidth according to the priority of the packet and network conditions, which can effectively solve the problem of network congestion that has been experienced by some queues for a long time. Experimental results show PPMF significantly outperforms other existing scheduling approaches in achieving 35–80% improvement on average time delay by adjusting the bandwidth adaptively, thus ensuring the transmission quality of the specified traffic and avoiding effectively network congestion.