Edge cloud computing can provide resources that are close to users and reduce response time. However, the edge cloud computing system still faces many challenges on addressing the overload problem due to its limited capacity. In this paper, a resource management strategy is proposed to satisfy the workloads of the edge cloud, while minimizing the financial cost of the rented nodes. Furthermore, the replica management strategy, which consists of the replica allocation and consistency preservation strategy, is studied. A dynamic replica allocation strategy is proposed to satisfy the user experience while reducing the storage overheads. In addition, the replica consistency preservation strategy is proposed for guaranteeing the data consistency and correctness. Finally, extensive experiments are conducted based on a real-world dataset. With the increase in the time, the proposed resource management algorithm can significantly reduce the total financial cost of the rented nodes and SLA default rate and improve the CPU utilization. For instance, the total financial cost of the proposed algorithm averagely achieves up to 32.27% and 53.65% reduction over that of CAAS algorithm and DRM algorithm, respectively. In addition, the proposed replica allocation algorithm can effectively reduce the data transmission time and the storage overhead.

边缘云计算可以提供接近用户的资源并减少响应时间。但是，边缘云计算系统由于容量有限而在解决过载问题方面仍然面临许多挑战。本文提出了一种资源管理策略，可以满足边缘云的工作量，同时最大程度地减少租用节点的财务成本。此外，还研究了由副本分配和一致性保存策略组成的副本管理策略。提出了一种动态副本分配策略来满足用户体验，同时减少存储开销。另外，提出了副本一致性保存策略，以保证数据的一致性和正确性。最后，基于真实世界的数据集进行了广泛的实验。随着时间的增加，所提出的资源管理算法可以显着降低租用节点的总财务成本和SLA违约率，并提高CPU利用率。例如，与CAAS算法和DRM算法相比，所提算法的总财务成本平均分别降低了32.27％和53.65％。另外，提出的副本分配算法可以有效减少数据传输时间和存储开销。分别。另外，提出的副本分配算法可以有效地减少数据传输时间和存储开销。分别。另外，提出的副本分配算法可以有效减少数据传输时间和存储开销。