학술논문

Fast Globally Optimal Computational Offloading and Service Caching in Container-Based Edge Computing Systems
Document Type
Periodical
Source
IEEE Internet of Things Journal IEEE Internet Things J. Internet of Things Journal, IEEE. 11(13):23780-23792 Jul, 2024
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Task analysis
Containers
Edge computing
Optimization
Resource management
Internet of Things
Image edge detection
Container
edge computing
service caching
task offloading
Language
ISSN
2327-4662
2372-2541
Abstract
Edge computing has become a new paradigm in response to the increasing demand for time-sensitive and computation-intensive tasks, offering advantages over traditional cloud computing due to its proximity to terminal devices and low transmission latency. Container-based edge computing provides a powerful way to deploy applications and manage resources at the edge of the network. However, optimizing the caching strategy is crucial due to the limited capacity of the edge server (ES), and the start-up time of services on ESs is a crucial consideration when making decisions regarding computation offloading and service caching. In this article, taking into account container start-up time, we formulate an optimization model for the task offloading, container caching, and image caching in the container-based edge computing architectures, which is a nonlinear integer programming (NLIP) problem that is NP-hard. We then propose an algorithm that finds the global optimal solution to this NLIP problem by transforming it into an equivalent linear integer programming problem. Our simulation experiments demonstrate that our proposed algorithm can effectively and fast find a globally optimal solution to the underlying problem and that our model outperforms the existing model without considering the container start-up time.