Advertisement
Published in:
2018 | OriginalPaper | Chapter
Towards Self-organizing Sensor Networks: Game-Theoretic \(\epsilon \)-Learning Automata-Based Approach
Authors : Jakub Gąsior, Franciszek Seredyński, Rolf Hoffmann
Published in: Cellular Automata
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
We consider a problem of lifetime optimization in Wireless Sensor Networks. The purpose of the system is to find a global activity schedule maximizing the lifetime of the Wireless Sensor Network while monitoring some area with a given measure of Quality of Service. The main idea of the proposed approach is to convert the problem of a global optimization into a problem of self-organization of a distributed multi-agent system, where agents take part in a game and search a solution in the form of a Nash equilibrium. We propose two game-theoretic models related to the problem of the lifetime optimization in Wireless Sensor Network and apply deterministic \(\epsilon \)-Learning Automata as players in the games. We present results of an experimental study showing the ability of reaching optimal solutions in the course of Learning Automata self-organization by local interactions in an iterated game.