Information Freshness in Multi-Hop Wireless Networks
Vishrant Tripathi, Rajat Talak, and Eytan Modiano

TL;DR
This paper develops and analyzes policies for minimizing information age in multihop wireless networks, introducing new methods that are practical, adaptable, and capable of handling complex network scenarios.
Contribution
It introduces three classes of policies—stationary randomized, age difference, and age debt—that optimize age of information in multihop wireless networks with various constraints.
Findings
Closed-form expressions for average AoI with stationary policies
Heuristic age difference policies improve local age management
Age debt policies handle complex cost functions and routing scenarios
Abstract
We consider the problem of minimizing age of information in multihop wireless networks and propose three classes of policies to solve the problem - stationary randomized, age difference, and age debt. For the unicast setting with fixed routes between each source-destination pair, we first develop a procedure to find age optimal Stationary Randomized policies. These policies are easy to implement and allow us to derive closed-form expression for average AoI. Next, for the same unicast setting, we develop a class of heuristic policies, called Age Difference, based on the idea that if neighboring nodes try to reduce their age differential then all nodes will have fresher updates. This approach is useful in practice since it relies only on the local age differential between nodes to make scheduling decisions. Finally, we propose the class of policies called Age Debt, which can handle 1)…
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 · Cognitive Functions and Memory
