Semantic Freshness Optimal Sampling and Transmission for Gossiping Receivers
2026-08-31 • Information Theory
Information TheoryNetworking and Internet Architecture
AI summaryⓘ
The authors study how to best decide when to sample new information from a source and when to send that information to two receivers who share updates with each other (gossip). They want to keep the information fresh (measured by Version Age of Information) while balancing the costs of sampling and sending data. By modeling the problem mathematically, they find patterns in the best strategies, such as sampling only when the information is old enough and sending updates first to the receiver with older information. They also show how link reliability and differences in information age between receivers affect these decisions.
Version Age of Information (VAoI)Markov Decision Process (MDP)sampling costtransmission costgossiping receiversRelative Value Iteration (RVI)optimal policylink reliabilityinformation freshnessthreshold policy
Authors
Irtiza Hasan, Ahmed Arafa
Abstract
We study the optimal joint sampling and transmission policy for a transmitter communicating with two gossiping receivers that share information with each other, with the objective of tracking a source under the Version Age of Information (VAoI) metric. The transmitter can observe source-version changes, but it has to pay a sampling cost to get the current source information content. Similarly, it can communicate with a receiver by paying a transmission cost. Gossiping enables local information exchange and is able to reduce costly direct transmissions. With imperfect communication links, we formulate an infinite-horizon average-cost Markov Decision Process (MDP) to jointly minimize receiver VAoI, sampling cost, and transmission cost. Using Relative Value Iteration (RVI), we evaluate the optimal policy and establish several properties of its structure. We prove that sampling has a threshold structure in the transmitter VAoI. Among direct transmissions, it is optimal to serve the older receiver. We further characterize the transmit or idle decision through the receiver VAoI difference. Our analysis shows that link reliability and receiver VAoI imbalance have a significant effect on the optimal policy structure. Numerical results verify the structural properties and demonstrate the performance gains of the optimal policy over multiple baselines.