A Self-Adaptable Network Topology for Ambient Intelligence

Abstract

Ambient Intelligence scenarios can be deployed even when the environment lacks of a underlying network infrastructure. This can be done using distributed ad-hoc networks. Ambient Intelligence applications can be highly variable and networks can have an unanticipated number of members. Inappropriate distributed network topologies can lead to unstable and inefficient communication. We propose PALTA, a decentralized and self-adaptable network topology. We use feedback loops to model its self-adaptable behaviour and we evaluate its performance using different simulations and measurements. PALTA allows the construction of distributed networks using self-management techniques and maintaining a good overall performance on the network communication.