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Adaptive Autonomy in Wireless Sensor Networks



Mirgita Frasheri , Jose Cano-Garcia , Eva Gonzalez-Parada , Baran Çürüklü, Mikael Ekström, Alessandro Papadopoulos, Cristina Urdiales

Publication Type:

Conference/Workshop Paper


International Conference on Autonomous Agents and Multi-Agent Systems


Moving nodes in a Mobile Wireless Sensor Network (MWSN) typically have two maintenance objectives: (i) extend the coverage of the network as long as possible to a target area, and (ii) extend the longevity of the network as much as possible. As nodes move and also route traffic in the network, their battery levels deplete differently for each node. Dead nodes lead to loss of connectivity and even to disengaging full parts of the network. Several reactive and rule-based approaches have been proposed to solve this issue by adapting redeployment to depleted nodes. However, in large networks a deliberative approach may increase performance by taking the evolution of node battery and traffic into account. In this paper, we present a hybrid agent-based architecture. Agents in each node collaborate and adapt their behaviour to their battery level. Agents are modeled through the willingness to interact abstraction, which defines when agents ask and give help to one another. Thus, depleting nodes may ask to be replaced by healthier counterparts and move to areas with less traffic or to a collection point. At the lower level, negotiations trigger a reactive navigation behaviour based on Social Potential Fields. Results show that the proposed method improves coverage and extends the longevity of the network in an environment without obstacles.


@inproceedings{Frasheri 5742,
author = {Mirgita Frasheri and Jose Cano-Garcia and Eva Gonzalez-Parada and Baran {\c{C}}{\"u}r{\"u}kl{\"u} and Mikael Ekstr{\"o}m and Alessandro Papadopoulos and Cristina Urdiales},
title = {Adaptive Autonomy in Wireless Sensor Networks},
month = {May},
year = {2020},
booktitle = {International Conference on Autonomous Agents and Multi-Agent Systems},
url = {}