Abstract:With the rapid development of video streaming services, scenarios in which large-scale users share bandwidth links increase unceasingly. The existing adaptive bitrate (ABR) algorithm used in dynamic adaptive streaming over HTTP (DASH) video streaming is mostly used to improve the quality of experience (QoE) of single-client customers, while some other algorithms are only for multi-client situations. This paper proposes a bandwidth scheduling algorithm for large-scale client situations. A clustering algorithm is adopted to reduce the scheduling scale. Then, bandwidth allocation is combined with the ABR algorithm to make bitrate decisions for clustering clients and thereby to improve bandwidth utilization and ensure a maximum overall QoE. Our experimental results show that compared with the bandwidth-sharing scheduling method, the method of scheduling the clustering client bandwidth and applying it to all clients achieves a 99.4% increase in overall user QoE. The overall QoE increase is 10.7% on that of the best state-of-the-art scheme Minerva.