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Joint optimization strategy for QoE-aware encrypted video caching and content distributing in multi-edge collaborative computing environment
Journal of Cloud Computing ( IF 3.418 ) Pub Date : 2020-10-02 , DOI: 10.1186/s13677-020-00204-8
Zhi Liu , Bo Qiao , Kui Fang

The video request service of users in 5G network will explode, and adaptive bit rate technology can provide users with reliable video response. Placing video resources on edge servers close to users can overcome the problem of excessive network load similar to traditional centralized cloud platform solutions. Moreover, multiple edge servers can provide caching and transcoding support by collaboration mechanisms, which further improves users’ Quality of Experience (QoE). However, the design difficulty of video caching and content distribution strategies is increased due to the diversity of collaboration mechanisms and the competition between local and collaborative services of edge servers for computing and storage resources. In order to solve this problem, video cache and content distribution problem is modeled as random integer programming problem in the multi-edge server at most two-hop collaboration scenario. In order to improve the security of video data transmission, the video stream is encrypted using an encryption algorithm based on Logistic chaotic-Quantum-dot Cellular Automata (QCA). For improving the efficiency of solving integer programming problems, this paper uses a pyramid intelligent evolution algorithm based on optimal cooperation strategy to solve this problem. Simulation experiments show that our proposed method can obtain higher QoE value compared with several newer methods. In addition, the average access delay of proposed method is shortened by more than 27.98%, which verifies its reliability.

中文翻译:

多边缘协作计算环境中QoE感知的加密视频缓存和内容分发的联合优化策略

5G网络中用户的视频请求服务将会爆炸性增长,自适应比特率技术可以为用户提供可靠的视频响应。将视频资源放置在靠近用户的边缘服务器上可以解决类似于传统集中式云平台解决方案的网络负载过大的问题。而且,多个边缘服务器可以通过协作机制提供缓存和转码支持,从而进一步提高了用户的体验质量(QoE)。但是,由于协作机制的多样性以及边缘服务器在本地和协作服务之间的计算和存储资源竞争,视频缓存和内容分发策略的设计难度增加了。为了解决这个问题,在最多两跳协作方案中,视频缓存和内容分发问题被建模为多边缘服务器中的随机整数编程问题。为了提高视频数据传输的安全性,使用基于Logistic混沌量子点元胞自动机(QCA)的加密算法对视频流进行加密。为了提高求解整数规划问题的效率,本文采用了基于最优合作策略的金字塔智能进化算法来解决该问题。仿真实验表明,与几种新方法相比,本文提出的方法可以获得更高的QoE值。此外,所提方法的平均访问延迟缩短了27.98%以上,证明了其可靠性。为了提高视频数据传输的安全性,使用基于Logistic混沌量子点元胞自动机(QCA)的加密算法对视频流进行加密。为了提高求解整数规划问题的效率,本文采用了基于最优合作策略的金字塔智能进化算法来解决该问题。仿真实验表明,与几种新方法相比,本文提出的方法可以获得更高的QoE值。此外,所提方法的平均访问延迟缩短了27.98%以上,证明了其可靠性。为了提高视频数据传输的安全性,使用基于Logistic混沌量子点元胞自动机(QCA)的加密算法对视频流进行加密。为了提高求解整数规划问题的效率,本文采用了基于最优合作策略的金字塔智能进化算法来解决该问题。仿真实验表明,与几种新方法相比,本文提出的方法可以获得更高的QoE值。此外,所提方法的平均访问延迟缩短了27.98%以上,证明了其可靠性。本文采用基于最优合作策略的金字塔智能进化算法来解决这一问题。仿真实验表明,与几种新方法相比,本文提出的方法可以获得更高的QoE值。此外,所提方法的平均访问延迟缩短了27.98%以上,证明了其可靠性。本文采用基于最优合作策略的金字塔智能进化算法来解决这一问题。仿真实验表明,与几种新方法相比,本文提出的方法可以获得更高的QoE值。此外,所提方法的平均访问延迟缩短了27.98%以上,证明了其可靠性。
更新日期:2020-10-02
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