Towards autonomous data ferry route design through reinforcement learning

Authors:
Daniel Henkel;Timothy X. Brown
Affiliations:
University of Colorado at Boulder, 80309, USA;University of Colorado at Boulder, 80309, USA
Venue:
WOWMOM '08 Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks
Year:
2008

Citing 0
Cited 5

Flying in the dark: controlling autonomous data ferries with partial observations

Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Enhancing the broadcast process in mobile ad hoc networks using community knowledge

Proceedings of the first ACM international symposium on Design and analysis of intelligent vehicular networks and applications
Review: Reinforcement learning for context awareness and intelligence in wireless networks: Review, new features and open issues

Journal of Network and Computer Applications
Dispatch-and-search: dynamic multi-ferry control in partitioned mobile networks

MobiHoc '11 Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing
On delay-minimized data harvesting with mobile elements in wireless sensor networks

Ad Hoc Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

Communication in delay tolerant networks can be facilitated by the use of dedicated mobile “ferries” which physically transport data packets between network nodes. The goal is for the ferry to autonomously find routes which minimize the average packet delay in the network. We prove that paths which visit all nodes in a round-trip fashion, i.e., solutions to the Traveling Salesman Problem, do not yield the lowest average packet delay. We propose two novel ferry path planning algorithms based on stochastic modeling and machine learning. We model the path planning task as a Markov Decision Process with the ferry acting as an independent agent. We apply Reinforcement Learning to enable the ferry to make optimal decisions. Simulation experiments show the resulting routes have lower average packet delay than solutions known to date.