DBLab School of Computer and Electrical Engineering KDBSL NTUA
Thursday, July 02, 2020
Τίτλος Evolutionary energy management and design of wireless sensor networks
Έγγραφο Προβολή εγγράφου
Συγγραφέας Dinos Ferentinos

We present an evolutionary optimization methodology for
self-organizing, adaptive wireless sensor network design and energy
management, taking into consideration application-specific requirements,
communication constraints and energy conservation characteristics. A
precision agriculture application of sensor networks is used as an example.
We use genetic algorithms as the optimization tool of the developed system
and an appropriate fitness function is developed to incorporate many
aspects of network performance. The design characteristics optimized by the
genetic algorithm system include the status of sensor nodes (whether they
are active or inactive), network clustering with the choice of appropriate
clusterheads and finally the choice between two signal ranges for the
regular sensor nodes. We show that optimal sensor network designs
constructed by the genetic algorithm system satisfy all
application-specific requirements, fulfill the existent connectivity
constraints and incorporate energy conservation characteristics. Energy
management is optimized to guarantee maximum life duration of the network
without lack of the required by the specific application network

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