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FROMS : a failure tolerant and mobility enabled multicast routing paradigm with reinforcement learning for WSNs

Förster, Anna ; Murphy, Amy L.

A growing class of wireless sensor network (WSN) applications require the use of sensed data inside the network at multiple, possibly mobile base stations. Standard WSN routing techniques that move data from multiple sources to a single, fixed base station are not applicable, motivating new solutions that efficiently achieve multicast. This paper explores in depth the requirements of this set...

Teaching networks how to learn : reinforcement learning for data dissemination in wireless sensor networks

Förster, Anna ; Murphy, Amy L. (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2009 ; 2009INFO001.

Wireless sensor networks (WSNs) are a fast developing research area with many new exciting applications arising, ranging from micro climate and environmental monitoring through health and structural monitoring to interplanetary communications. At the same time researchers have invested a lot of time and effort into developing high performance energy efficient and reliable communication protocols...