Publications:Multi-agents supporting reflection in a middleware for mission-driven heterogeneous sensor networks

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Title Multi-agents supporting reflection in a middleware for mission-driven heterogeneous sensor networks
Author Edison Pignaton de Freitas and Marco Aurélio Wehrmeister and Armando Morado Ferreira and Carlos Eduardo Pereira and Tony Larsson
Year 2009
PublicationType Conference Paper
Journal
HostPublication Proc. of 3rd Agent Technology for Sensor Networks (ATSN), in conjunction with 8th AAMAS
DOI
Conference Third International Workshop on Agent Technology for Sensor Networks (ATSN-09). A workshop of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-09), 12th May, Budapest, Hungary
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:408014
Abstract The emerging applications using sensor networks technologies constitute a new trend requiring several different devices to work together and this partly autonomously. However, the integration and coordination of heterogeneous sensors in these emerging systems is still a challenge, especially when the target application scenario is susceptible to constant changes. Such systems must adapt themselves in order to fulfill requirements that can also change during the system runtime. Due to the dynamicity of this context, system adaptations must take place very quickly, requiring system autonomous decisions to perform them without any human operator intervention, besides the first directions to the system. Thus a reflective behavior must be provided. This paper presents a reflective middleware that supports reflective behaviors to address adaptation needs of heterogeneous sensor networks deployed in dynamic scenarios. This middleware presents specific handling of users’ requirements by representing them as missions that the network must accomplish with. These missions are then translated to network parameters and distributed over the network by means of the reasoning about network nodes capabilities and environment conditions. A multi- agent approach is proposed to perform this initial reasoning as well as the adaptations needed during the system runtime.