Abstract
Live streaming service usually delivers the content in mobile edge computing (MEC) to reduce the network latency and save the backhaul capacity. Considering the limited resources, it is necessary that MEC servers collaborate with each other and form an overlay to realize more efficient delivery. The critical challenge is how to optimize the topology among the servers and allocate the link capacity so that the cost will be lower with delay constraints. Previous approaches rarely consider server collaborations for live streaming service, and the scheduling delay is usually ignored in MEC, leading to suboptimal performances. In this paper, we propose a popularity-guided overlay model which takes the scheduling delay into consideration and utilizes MEC collaboration to achieve efficient live streaming service. The links and servers are shared among all channel streams and each stream is pushed from cloud servers to MEC servers via the trees. Considering the optimization problem is NP-hard, we propose an effective optimization framework called cost optimization for live streaming (COLS) to predict the channel popularity by a LSTM model with multiscale input data. Finally, we compute topology graph by greedy scheme and allocate the capacity with convex programming. Experimental results show that the proposed approach achieves higher prediction accuracy, reducing the capacity cost by more than 40% with an acceptable delay compared with state-of-the-art schemes.
Highlights
With the rapid popularization of smart devices, the Internet traffic has ushered an explosive growth [1], and almost 82% of all network traffic comes from video traffic [2]
Some approaches [20, 21] use both the popularity and retention rate of video streams to maximize video bitrate for efficient utilization of bandwidth. Distinguished from these approaches which emphasize bitrate adaptation, this paper focuses on the topology optimization for the cooperation of mobile edge computing (MEC) servers while considering the scheduling delay to achieve lower link capacity with delay constraints
The MEC server gives up delivering some channels to save the link capacity
Summary
With the rapid popularization of smart devices, the Internet traffic has ushered an explosive growth [1], and almost 82% of all network traffic comes from video traffic [2]. The increasing traffic puts amounts of pressure on the cloud data center, bringing more difficulties for the optimization of the servers [3], especially for some latency-sensitive services, e.g., live streaming. Mobile edge computing (MEC) is brought in as a new technology for live streaming service to reduce the network latency and alleviate the backhaul capacity [4]. Internet service provider (ISP) places nearby MEC servers at the network edge so that users can visit these servers instead of remote cloud servers and get a better experience. The cost of deploying such an overlay mainly comes from the link capacity cost
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