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Distribution of teaching surveillance video via edge computing
Author(s) -
Wu Zhengxiu,
Song Echo
Publication year - 2020
Publication title -
internet technology letters
Language(s) - English
Resource type - Journals
ISSN - 2476-1508
DOI - 10.1002/itl2.234
Subject(s) - computer science , cache , edge computing , enhanced data rates for gsm evolution , multimedia , bandwidth (computing) , computer network , mobile edge computing , network architecture , low latency (capital markets) , real time computing , telecommunications
The generation, processing and distribution of multimedia data from video are increasingly toward the edge of the network with the development of mobile and industrial network. The uncertainty of user behavior and limited system resources have become a major challenge for network video services, for example, the distribution of teaching surveillance video. It is a hot spot to support network video services and content distribution with lower latency and higher bandwidth requirements by using the computing, storage, and network resources at the edge of network. In this paper, we first analyze the challenges which are faced in video distribution based on edge computing; then propose a framework for teaching surveillance video content distribution through the network, storage, and computing capabilities of edge computing; lastly provide an edge caching architecture and a cache update strategy by using a LSTM network. The experimental results demonstrate the proposed framework is more efficient than previous ones.