提出移动边缘计算环境下增强自适应比特流视频缓存传输方案。首先针对网络效用最大化问题提出基于改进的K-means算法对移动用户进行动态分组,解决码率分配子问题;然后将缓存策略和无线资源联合分配归纳为一个多对多匹配问题,同时通过等效带宽,用户可以根据时变信道选择无线链路,灵活地调整实际传输比特率版本。仿真实验结果表明,MEC-ABR方案与其他方案相比,能够同时提高缓存命中率和吞吐量。
Abstract
In the paper,an enhanced Adaptive Bit Rate (ABR) video cache delivery scheme for MEC environments is proposed.Firstly,it proposes the dynamic grouping of mobile users based on the improved K-means algorithm for network utility maximization to solve the sub-problem of code rate allocation.Then,the cache strategy and wireless resource joint allocation are summarized as a many-to-many matching problem.At the same time,through equivalent bandwidth,users can select wireless links based on time-varying channels and flexibly adjust the actual delivery bit rate version.The simulation results show that the MEC-ABR scheme can improve the cache hit ratio and throughput from caching at the same time.
关键词
移动边缘计算 /
自适应比特流 /
视频缓存传输 /
等效带宽
Key words
MEC /
ABR /
video cache delivery /
equivalent bandwidth
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参考文献
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基金
* 贵州省科技厅基础研究计划(自然科学)项目-贵州典型受限空间端射天线系统研究(ZK(2022)528);贵州省教育厅青年科技人才成长项目-边缘计算环境下车联网的高效隐私保护机制(黔教合KY字〔2019〕144);六盘水师范学院科研项目-基于边缘计算的网联车协同路径规划与资源分配研究(LPSSYYBZK202207);六盘水师范学院教改项目-人工智能背景下基于OBE理念的Python编程课程教学改革研究(LPSSYjg-2021-29)。
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