학술논문

Multi-Criteria Optimization of Application Offloading in the Edge-to-Cloud Continuum
Document Type
Conference
Source
2023 62nd IEEE Conference on Decision and Control (CDC) Decision and Control (CDC), 2023 62nd IEEE Conference on. :4917-4923 Dec, 2023
Subject
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Performance evaluation
Cloud computing
Computational modeling
Minimization
Mathematical models
Software
Regulation
Language
ISSN
2576-2370
Abstract
Applications are becoming increasingly data-intensive, requiring significant computational resources to meet their demand. Cloud-based services are insufficient to meet such demand, leading to a shift of the computation towards the devices closer to the edge of the network, leading to the emergence of an Edge-to-Cloud computing Continuum (E2C). An application can offload part of its computation toward the E2C. The allocation of applications to a set of available computing nodes is a challenging problem, as the allocation needs to take into account several factors, including the application requirements and demands as well as the optimization of the resource utilization in the E2C infrastructure and the minimization the CO 2 footprint of the executed applications. Control and optimization techniques provide a vast array of tools for optimizing the Edge-to-Cloud continuum's management. This paper provides a mathematical formulation for the application offloading with specific requirements in the cloud computing domain. The problem is modeled as integer linear programming and constraint programming models and implemented in commercially available software. Finally, we provide the results of performed comparison between the two models.