The Cost of Delay in Status Updates and their Value: Non-linear Ageing
Not on the map. Why?
Abstract (arXiv)
We consider a status update communication system consisting of a source-destination link. A stochastic process is observed at the source, where samples are extracted at random time instances, and delivered to the destination, thus, providing status updates for the source. In this paper, we expand the concept of information ageing by introducing the cost of update delay (CoUD) metric to characterize the cost of having stale information at the destination. The CoUD captures the freshness of the information at the destination and can be used to reflect the information structure of the source. Moreover, we introduce the value of information of update (VoIU) metric that captures the reduction of CoUD upon reception of an update. Using the CoUD, its by-product metric called peak cost of update delay (PCoUD), and the VoIU, we evaluate the performance of an M/M/1 system in various settings that consider exact expressions and bounds. Our results indicate that the performance of CoUD differs depending on the cost assigned per time unit, however the optimal policy remains the same for linear ageing and varies for non-linear ageing. When it comes to the VoIU the performance difference appears only when the cost increases non-linearly with time. The study illustrates the importance of the newly introduced variants of age, furthermore supported in the case of VoIU by its tractability.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Dec 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1; 2026: 1.
5 papers.
- 2024Version age-based client scheduling policy for federated learningcited by 5
- 2023Value of Information and Timing-aware Scheduling for Federated Learningcited by 3
- 2022To Compute or not to Compute? Adaptive Smart Sensing in Resource-Constrained Edge Computingcited by 1
- 2025SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Modelscited by 1
- 2026Chronofy: A Temporal-Logical Decay Architecture for Information Validity in Time-Aware Retrieval-Augmented Generationcited by 0
- 2026Chronofy: A Temporal-Logical Decay Architecture for Information Validity in Time-Aware Retrieval-Augmented Generation17 Jul 2026
- 2025SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Models25 Feb 2025
- 2024Version age-based client scheduling policy for federated learning8 Feb 2024
- 2023Value of Information and Timing-aware Scheduling for Federated Learning16 Dec 2023
- 2022To Compute or not to Compute? Adaptive Smart Sensing in Resource-Constrained Edge Computing5 Sep 2022