Volume 48 Issue 3
Mar.  2022
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LIU Haipeng, ZHOU Shuqiu. Application analysis of multi-access edge computing in intelligent mine network[J]. Journal of Mine Automation,2022,48(3):26-31.  doi: 10.13272/j.issn.1671-251x.2021100004
Citation: LIU Haipeng, ZHOU Shuqiu. Application analysis of multi-access edge computing in intelligent mine network[J]. Journal of Mine Automation,2022,48(3):26-31.  doi: 10.13272/j.issn.1671-251x.2021100004

Application analysis of multi-access edge computing in intelligent mine network

doi: 10.13272/j.issn.1671-251x.2021100004
  • Received Date: 2021-10-08
  • Accepted Date: 2022-03-07
  • Rev Recd Date: 2022-03-06
  • Available Online: 2022-03-10
  • In order to solve the problems of various types, complex system and low resource sharing rate of software and hardware equipment, difficult network upgrading and transformation, and the incapability to meet the requirements of vertical services due to limited uplink and downlink transmission bandwidth and long total service delay, this paper proposes to introduce multi-access edge computing(MEC) technology into mine network to provide support for the realization of intelligent mine. For the intelligent mine service types of video monitoring, delay sensitive and connection, the application mode of MEC is discussed, and the characteristics of MEC supporting multiple protocols and equipment access are analyzed. It is pointed out that MEC is the only choice to provide integrated management and control based on the existing underground multiple protocols and equipment, and is the best solution to provide undifferentiated high-quality end-to-end service for users. The intelligent mine network computing tree model based on business requirements is established, and its evolution is divided into three stages, namely Pre-5G, 5G and Beyond-5G(6G). The main characteristics and symbolic technologies of each stage are analyzed, as well as the business characteristics such as load balance, business mobility, data security, scalability and integration characteristics. It is pointed out that each characteristic is the worst in the first stage and the best in the third stage. However, there is still a gap to achieve the goal of truly universal hardware devices and fully standardized interfaces. Combined with the computing tree model, the intelligent mine network MEC deployment model is proposed. It is pointed out that the model is based on a three-level flat structure with depth of 2, which can give full play to the edge computing capability of nodes at all levels, and dynamically select task unloading strategy while taking into account the load balance of nodes, so as to complete efficient task coordination. Moreover, the functions of nodes can be selected and flexibly deployed according to the actual situation on the ground or underground, which is suitable for all stages of intelligent mine construction.

     

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