
Abstract Big data will cause the system for business public opinion to be overburdened, and dynamic changes in computing resources will cause tasks to be delayed. To end the situation, this study assigns non-fixed execution time to each task node based on the task soft deadline and task constraints and solves the problem of difficult task scheduling caused by task dependency constraints. Aiming at the problem of task delay caused by dynamic changes of computing resources, this paper proposes an adaptive offloading and scheduling algorithm for dependent tasks in the mobile edge computing environment. This study takes the economic efficiency analysis system as an example and uses the resource allocation management algorithm based on linked lists and edge servers to study the communication resource allocation management of the economic efficiency analysis system. In addition, this study designs experiments to perform performance analysis of the algorithm proposed by this study. The research results show that the proposed algorithm has an obvious effect.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 10 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
