mdh.sePublications
4748495051525350 of 68
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Adaptive Autonomy in Wireless Sensor Networks
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (Robotics)
University of Malaga, Spain.
University of Malaga, Spain.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (Robotics)ORCID iD: 0000-0002-5224-8302
Show others and affiliations
2020 (English)Conference paper, Published paper (Refereed)
Abstract [en]

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 cooperative 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 that addresses the problem of depleting nodes during the maintenance phase of a MWSN. Agents, each assigned to a node, collaborate and adapt their behaviour to their battery levels. The collaborative behavior is 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 (SPF). It is shown that the proposed method improves coverage and extends network longevity in an environment without obstacles as compared to SPF alone.

Place, publisher, year, edition, pages
2020.
Keywords [en]
self-organisation; multi-robot systems; networked systems and dis-tributed robotics
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-47904OAI: oai:DiVA.org:mdh-47904DiVA, id: diva2:1428871
Conference
19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'20)
Available from: 2020-05-06 Created: 2020-05-06 Last updated: 2020-05-07Bibliographically approved
In thesis
1. Modelling and Control of the Collaborative Behavior of Adaptive Autonomous Agents
Open this publication in new window or tab >>Modelling and Control of the Collaborative Behavior of Adaptive Autonomous Agents
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Research on autonomous agents and vehicles has gained momentum in the past years, which is reflected in the extensive body of literature and the investment of big players of the industry in the development of products such as self-driving cars. Additionally, these systems are envisioned to continuously communicate and cooperate with one another in order to adapt to dynamic circumstances and unforeseeable events, and as a result will they fulfil their goals even more efficiently.The facilitation of such dynamic collaboration and the modelling of interactions between different actors (software agents, humans) remains an open challenge.This thesis tackles the problem of enabling dynamic collaboration by investigating the automated adjustment of autonomy of different agents, called Adaptive Autonomy (AA). An agent, in this context, is a software able to process and react to sensory inputs in the environment in which it is situated in, and is additionally capable of autonomous actions. In this work, the collaborative adaptive autonomous behaviour of agents is shaped by their willingness to interact with other agents, that captures the disposition of an agent to give and ask for help, based on different factors that represent the agent's state and its interests.The AA approach to collaboration is used in two different domains: (i) the hunting mobile search problem, and (ii) the coverage problem of mobile wireless sensor networks. In both cases, the proposed approach is compared to state-of-art methods.Furthermore, the thesis contributes on a conceptual level by combining and integrating the AA approach -- which is purely distributed -- with a high-level mission planner, in order to exploit the ability of dealing with local and contingent problems through the AA approach, while minimising the requests for a re-plan to the mission planner.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2020
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 314
National Category
Engineering and Technology Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-47905 (URN)978-91-7485-468-8 (ISBN)
Public defence
2020-06-12, Västerås Campus (+ Online/Zoom), Mälardalens högskola, Västerås, 10:00 (English)
Opponent
Supervisors
Available from: 2020-05-08 Created: 2020-05-06 Last updated: 2020-05-13Bibliographically approved

Open Access in DiVA

fulltext(1720 kB)4 downloads
File information
File name FULLTEXT01.pdfFile size 1720 kBChecksum SHA-512
e3c59b8938a6995ce69a06e3c2df8a3920a2990eff552dd09153ad70ce1fd3c8b3a2362d16d8b60be7d35267802ea3471d162c7fdd1292de57757189f9286513
Type fulltextMimetype application/pdf

Authority records BETA

Frasheri, MirgitaCuruklu, BaranEkström, MikaelPapadopoulos, Alessandro

Search in DiVA

By author/editor
Frasheri, MirgitaCuruklu, BaranEkström, MikaelPapadopoulos, Alessandro
By organisation
Embedded Systems
Engineering and TechnologyComputer Systems

Search outside of DiVA

GoogleGoogle Scholar
Total: 4 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 25 hits
4748495051525350 of 68
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf