Learning based gain-aware content dissemination in delay tolerant networks

Abstract

This paper presents a multicast Delay Tolerant Network (DTN) routing protocol with the goal of maximizing an economic gain for Device-to-Device (D2D) commercial content dissemination. The defined economic gain is a composite routing performance index, which combines revenue from delivery, and forwarding cost from disseminating commercial content such as coupons. Majority of existing approaches, due to lack of gain-awareness, cannot control the economic gain of dissemination, as defined in this context. In the proposed approach, which is inspired by Q-learning, nodes are able to learn a set of forwarding actions which lead to a higher expected reward, i.e., gain. Due to the online learning framework, this Q-learning based Gain-aware Routing (QGR) protocol is expected to be robust in diverse and dynamic mobility environments. Using the DTN simulation software ONE, we run experiments for functional validation and performance evaluation of the proposed protocol with respect to two existing competitive protocols under different protocol constraints and mobility scenarios.