Edge Computing in an IoT Base Station System: Reprogramming and Real-Time Tasks

Huifeng Wu, Junjie Hu, Jiexiang Sun and Danfeng Sun

Complexity, 2019, vol. 2019, 1-10

Abstract:

There are millions of base stations distributed across China, each containing many support devices and monitoring sensors. Conventional base station management systems tend to be hosted in the cloud, but cloud-based systems are difficult to reprogram and performing tasks in real-time is sometimes problematic, for example, sounding a combination of alarms or executing linked tasks. To overcome these drawbacks, we propose a hybrid edge-cloud IoT base station system, called BSIS. This paper includes a theoretical mathematical model that demonstrates the dynamic characteristics of BSIS along with a formulation for implementing BSIS in practice. Embedded programmable logic controllers serve as the edge nodes; a dynamic programming method creates a seamless integration between the edge nodes and the cloud. The paper concludes with a series of comprehensive analyses on scalability, responsiveness, and reliability. These analyses indicate a possible 60% reduction in the number of alarms, an edge response time of less than 0.1s, and an average downtime ratio of 0.66%.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:4027638

DOI: 10.1155/2019/4027638

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