AoIT-Empowered Associated Network Slicing: Resource Orchestration for Joint Monitoring
Year: 2024
Type: article
Abstract: Joint monitoring, by integrating observations from multiple types of equipment, is essential for a thorough understanding of physical processes in the Industrial Internet of Things (IIoT). However, it does demand sufficient resources to ensure reliable and timely delivery of such observations. Although network slicing is widely used to meet such heterogeneous requirements, it falls short in this system, because it causes interconnected impacts on system performance across multiple slices. In this paper, we introduce an innovative associated network slicing framework for joint monitoring, which focuses on system cost minimization while accounting for slice associations. Particularly, to better understand the characteristics, we introduce a new concept, Age of Inexact Task (AoIT), to capture inter-slice associations. We then decompose the optimization variables to facilitate efficient Associated Network Slicing (ANS) algorithmic design, leading to a closed-form solution for intra-slice small-timescale resource allocation and an iterative block coordinate gradient descent algorithm for inter-slice large-timescale resource allocation. Simulation results demonstrate that our proposed ANS balances heterogeneous requirements and associations, showing significant reductions in system costs compared to existing solutions.
Institutions: Shanghai Jiao Tong University, City University of Hong Kong
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4402039848