Distributed Backlog-Aware D2D Communication for Heterogeneous IIoT Applications
Hossam Farag, Cedomir Stefanovic, Mikael Gidlund

TL;DR
This paper proposes a distributed backlog-aware D2D communication protocol for heterogeneous IIoT networks, optimizing the Age-of-Information while considering delay constraints through an analytical framework and numerical analysis.
Contribution
It introduces a novel distributed backlog-aware access protocol and provides an analytical framework for optimizing AoI under delay constraints in IIoT networks.
Findings
The protocol improves AoI performance in heterogeneous IIoT networks.
Analytical models accurately evaluate delay and AoI metrics.
Numerical results identify optimal parameters for AoI minimization.
Abstract
Delay and Age-of-Information (AoI) are two crucial performance metrics for emerging time-sensitive applications in Industrial Internet of Things (IIoT). In order to achieve optimal performance, studying the inherent interplay between these two parameters in non-trivial task. In this work, we consider a Device-to-Device (D2D)-based heterogeneous IIoT network that supports two types of traffic flows, namely AoI-orientated. First, we introduce a distributed backlog-aware random access protocol that allows the AoI-orientated nodes to opportunistically access the channel based on the queue occupancy of the delay-oriented node. Then, we develop an analytical framework to evaluate the average delay and the average AoI, and formulate an optimization problem to minimize the AoI under a given delay constraint. Finally, we provide numerical results to demonstrate the impact of different network…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAge of Information Optimization · IoT Networks and Protocols · IoT and Edge/Fog Computing
