Security and performance-aware resource allocation for enterprise multimedia in mobile edge computing
Security and performance-aware resource allocation for enterprise multimedia in mobile edge computing
复制标题
移动边缘计算中企业多媒体的安全和性能感知资源分配
DOI：
10.1007/s11042-019-08557-2
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发表时间：
2020-01
影响因子：
3.6
通讯作者：
Huang Liguo
中科院分区：
文献类型：
--
作者：
Li Zhongjin;Hu Haiyang;Huang Binbin;Chen Jie;Li Chuanyi;Hu Hua;Huang Liguo
移动的边缘计算（MEC）是一种有前途的计算模型，并且已经获得了显著的普及，因为它部署了资源（例如，计算、网络和存储）提供给演进节点B（eNB）以提供巨大的益处，诸如低延迟和能耗。越来越多的企业构建其边缘计算平台来存储多媒体内容（即，视频、音频、照片和文本数据）。然而，当经由无线网络发送或接收多媒体数据时，eNB和UE都将经历严重的安全攻击。现有的MEC研究主要集中在任务卸载和性能改进，而没有考虑企业多媒体安全问题。提出了一种面向MEC环境的企业多媒体安全性能感知资源分配算法（Spara）。更具体地说，我们首先建立了企业多媒体安全的体系结构，用于向UE发送数据请求，主要包括计算和带宽资源分配。然后，我们制定的随机数据传输问题，以尽量减少延迟和能量消耗的UE的安全保证。为了实现这一目标，两个队列，即前端队列和后端队列，用于每个UE，并应用李亚普诺夫优化技术来确定如何分配计算和带宽资源。严格的理论分析表明，Spara算法满足[O（1/V），O（V）]的能量-延迟权衡。大量的仿真实验验证了分析结果和Spara算法的有效性。
Mobile edge computing (MEC) is a promising computing model and has gained remarkable popularity, as it deploys the resources (e.g., computation, network, and storage) to the evolved NodeB (eNB) to provide enormous benefits such as low delay and energy consumption. More and more enterprises construct their edge computing platforms to store multimedia contents (i.e., video, audio, photos, and text data) for the user equipment (UE). However, both the eNB and UEs will experience serious security attacks when transmitting or receiving multimedia data via the wireless network. Existing MEC studies mainly focus on task offloading and performance improvement without considering the enterprise multimedia security problem. This paper proposes a security and performance-aware resource allocation (Spara) algorithm for enterprise multimedia in MEC environment. More specifically, we first build the architecture of enterprise multimedia security for sending the data requests to UEs, which mainly consists of computing and bandwidth resource allocation. Then, we formulate the stochastic data transmission problem to minimize the delay and energy consumption of UEs subject to the security guarantee. To achieve this goal, two queues, namely front-end queue and back-end queue, are used for each UE, and the Lyapunov optimization technique is applied to determine how to allocate the computing and bandwidth resources. Rigorous theoretical analysis shows that Spara algorithm meets the [O(1/V),O(V)] energy-delay tradeoff. Extensive simulation experiments validate this analysis result and the effectiveness of Spara algorithm.
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