Abstract
Mobile users’ demands to delay-sensitive video streaming media put forward new requirements for mobile networks, such as architecture optimization. Edge caching as a new paradigm is proposed to enhance the quality of service (QoS) for mobile users at the network edge. Due to the limited coverage of edge cache nodes, the frequent handoffs between base stations would aggravate network traffic overhead, resulting in a bad experience of high latency and service interruption when mobile users browse videos. This paper first proposes a three-layer mobile edge network architecture and applied edge caching to video streams to build an efficient caching system. Given the user’s mobility and low latency of mobile video streaming, we propose an edge caching strategy based on user speed and content popularity. Horizontally, the user’s speed affects the spanning area and the buffer size of the cache on edge; vertically, content popularity determines the priority of cached videos. Experimental results demonstrate that our caching strategy outperforms other schemes in terms of the average delay and the cache hit ratio in mobile video streaming scenes compared with the other three classic caching methods.
Highlights
With the rapid development of mobile devices and network technology, we are experiencing an era of explosive mobile data traffic
Due to the different popularity and bit rate of video content, we set the size of the video content package in the simulation experiment to 500 MB to 1000 MB
The pre-caching strategy of CCMP based on PPM ignores the influence of different speeds of mobile users
Summary
With the rapid development of mobile devices and network technology, we are experiencing an era of explosive mobile data traffic. Using edge caching strategies to improve mobile video streaming services currently faces the following problems: (1) When the user path is known, arranging the base stations on the route to buffer appropriate video content to minimize the average delay is the key to improving the QoE. When the user path is known, we integrate and optimize the caching mechanism of mobile video streams from the perspectives of video popularity and user movement speed This strategy can significantly reduce the high delay caused by user movement and service interruption caused by the handoffs between base stations.
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