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Issue - 2019 (2019) Trang:
Tạp chí: IEEE Transactions on Network and Service Management

A collaborative integration between cloud and edge computing is proposed to be able to exploit the advantages of both technologies. However, most of the existing studies have only considered two-tier cloud-edge computing systems which merely support vertical offloading between local edge nodes and remote cloud servers. This paper thus proposes a generic architecture of cloud-edge computing with the aim of providing both vertical and horizontal offloading between service nodes. To investigate the effectiveness of the design for different operational scenarios, we formulate it as a workload and capacity optimization problem with the objective of minimizing the system computation and communication costs. Because such a mixed-integer nonlinear programming (MINLP) problem is NP-hard, we further develop an approximation algorithm which applies a branch-and-bound method to obtain optimal solutions iteratively. Experimental results show that such a cloud-edge computing architecture can significantly reduce total system costs by about 34%, compared to traditional designs which only support vertical offloading. Our results also indicate that, to accommodate the same number of input workloads, a heterogeneous service allocation scenario requires about a 23% higher system costs than a homogeneous scenario.

Các bài báo khác
(2016) Trang:
Tạp chí: 2016 IEEE International Conference on Communications ( (ICC)), 23-27 May 2016, Kuala Lumpur - Malaysia,
(2017) Trang:
Tạp chí: 2017 IEEE International Conference on Communications (ICC), 21-25 May 2017, Paris - France
31 (2018) Trang:
Tạp chí: International Journal of Communication Systems
 


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