Towards Optimal Application Offloading in Heterogeneous Edge-Cloud Computing

IEEE TRANSACTIONS ON COMPUTERS(2023)

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Abstract
Application offloading plays a crucial role in application deployment in edge-cloud computing. However, finding the optimal solution for application offloading is challenging due to the heterogeneous resources, computing dependency of tasks, and complex network. Existing research on application offloading problems often assumes that the communication delay between the edge and the cloud (inter-side) is symmetrical or that within the cloud or edge (intra-side) can be omitted. However, this assumption is not practical considering the distinct features of the clouds and the edge clusters. Therefore, we study application offloading in the heterogeneous edge-cloud environment by considering both intra-side communication delay between tasks assigned to the same side and asymmetry inter-side communication delay between edge and cloud sides. We first focus on the specific circumstances with a boundary condition that lead to an optimal offloading solution in a heterogeneous edge-cloud environment. Then we study the general case by designing an iterative algorithm with maximum gain technique to solve it. Furthermore, considering various bandwidths within each side and resource capacities of physical nodes, we develop two efficient algorithms by combining minimum cut and maximum gain approaches. Both simulations and real trace-based evaluations are conducted to validate that the proposed algorithms outperform existing solutions.
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Key words
Task analysis,Delays,Cloud computing,Computational modeling,Boundary conditions,Costs,Iterative methods,Application offloading,cloud computing,edge computing,minimum cut
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