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.

Decentralized Self-Adaptive Systems: A Mapping Study

“…The dominating motivation for decentralizing the self-adaptation logic is the nature of the problem (41 studies). For instance, in [34], the authors consider ad-hoc distributed networks where the topology and routing in the network is inherently organized on a peer to peer basis. In [41], the authors argue that modern computing systems are characterized by an increasing level of complexity and uncertain changes, requiring the need for a decentralized self-adaptation solution.…”

Identifying aspects of Ambient Intelligence through a review of recent developments

“…In [37], the authors propose PALTA: Peer-to-peer Adaptable Topology for Ambient intelligence, in order to develop a system more acceptable to humans, enabled by basic machine learning methods that allow it to learn by observing users. A decentralized and self-adaptable network topology is used.…”