Self-management of ambient intelligence systems: a pure agent-based approach
Inmaculada Ayala, Mercedes Arana Amor, Lidia Fuentes
Abstract
Inmaculada Ayala, Mercedes Arana Amor, Lidia Fuentes
Abstract
Ambient Intelligence systems (AmI) are normally composed of networked heterogeneous devices with critical resource limitations. One of the biggest requirements of AmI systems is that they should be capable of self-management in order to adapt their behavior and resources to environmental conditions and variable device resources. Autonomous agents are a good option to endow AmI systems with self-managing capabilities, but current agent platform implementations do not adequately address the heterogeneity requirements of AmI systems, given the impossibility until now of producing pure agent-based solutions. In this paper we present a pure agent-based solution for self-managing AmI systems, with particular emphasis on defining a working solution considering the diversity of devices and communication protocols through which AmI devices must interoperate. Categories and Subject Descriptors
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Ambient Intelligence systems (AmI) are normally composed of networked heterogeneous devices with critical resource limitations. One of the biggest requirements of AmI systems is that they should be capable of self-management in order to adapt their behavior and resources to environmental conditions and variable device resources. Autonomous agents are a good option to endow AmI systems with self-managing capabilities, but current agent platform implementations do not adequately address the heterogeneity requirements of AmI systems, given the impossibility until now of producing pure agent-based solutions. In this paper we present a pure agent-based solution for self-managing AmI systems, with particular emphasis on defining a working solution considering the diversity of devices and communication protocols through which AmI devices must interoperate. Categories and Subject Descriptors
Key concepts: Interoperability, Computer science, Ambient intelligence, Implementation, Multi-agent system, Impossibility, Distributed computing, Resource management (computing)