Deadline-constrained security-aware workflow scheduling in hybrid cloud architecture
2025 (English)In: Future Generation Computer Systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 162, article id 107466Article in journal (Refereed) Published
Abstract [en]
A hybrid cloud is an efficient solution to deal with the problem of insufficient resources of a private cloud when computing demands increase beyond its resource capacities. Cost-efficient workflow scheduling, considering security requirements and data dependency among tasks, is a prominent issue in the hybrid cloud. To address this problem, we propose a mathematical model that minimizes the monetary cost of executing a workflow and satisfies the security requirements of tasks under a deadline. The proposed model fulfills data dependency among tasks, and data transmission time is formulated with exact mathematical expressions. The derived model is a Mixed-integer linear programming problem. We evaluate the proposed model with real-world workflows over changes in the input variables of the model, such as the deadline and security requirements. This paper also presents a post-optimality analysis that investigates the stability of the assignment problem. The experimental results show that the proposed model minimizes the cost by decreasing inter-cloud communications for dependent tasks. However, the optimal solutions are affected by the limitations that are imposed by the problem constraints.
Place, publisher, year, edition, pages
Elsevier B.V. , 2025. Vol. 162, article id 107466
Keywords [en]
Cost minimization, Hybrid cloud, Mixed integer linear programming, Sensitivity analysis, Workflow scheduling, Cloud computing architecture, Combinatorial optimization, Cost benefit analysis, Cryptography, Integer programming, Data dependencies, Hybrid clouds, Integer Linear Programming, Mixed integer linear, Security requirements, Security-aware, Work-flows
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-68213DOI: 10.1016/j.future.2024.07.044ISI: 001295842500001Scopus ID: 2-s2.0-85201083709OAI: oai:DiVA.org:mdh-68213DiVA, id: diva2:1891076
2024-08-212024-08-212024-09-04Bibliographically approved