A Communication-Contention-Aware Privacy-Preserving Workflow Scheduling Method for Geo-Distributed Datacenters

Document Type

Article

Publication Date

1-1-2024

Abstract

Owing to real-world demands for global collaboration and increasing volumes of data to be analyzed, many data-intensive workflow applications are deployed in geographically distributed (geo-distributed) datacenters (DCs). In such an environment, inter-DC bandwidths are much slower than intra-DC ones, and how to effectively schedule inter-DC data communication without contention is crucial to a workflow's execution time. Meanwhile, the diversity of data privacy requirements in geo-distributed DCs causes an additional challenge. This article introduces a workflow scheduling model for geo-distributed DCs where inter-DC communications are explicitly considered and data privacy must be protected. A Communication-contention-Aware Privacy-preserving Scheduling (CAPS) method is proposed to solve it for the first time. CAPS distributes workflow tasks to DCs via a simulated annealing method such that privacy constraints are respected and the overall inter-DC data transmission time is minimized. It adopts a list scheduling heuristic to schedule tasks and data communications to computation and network resources. In experiments, CAPS is compared against leading-edge methods with realistic workflows and network settings. The results reveal that it can reduce workflow makespan by 7.08-87.53% in comparison with its peers, while guaranteeing data privacy and resolving all the communication contention issues, which has not been seen in the existing work.

Identifier

85195365154 (Scopus)

Publication Title

IEEE Transactions on Services Computing

External Full Text Location

https://doi.org/10.1109/TSC.2024.3407595

e-ISSN

19391374

First Page

1887

Last Page

1898

Issue

5

Volume

17

Grant

62172065

Fund Ref

National Natural Science Foundation of China

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