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Towards a Decentralized and Self-Adaptive System for M-Learning Applications
Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM. (CeLeKT)
Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.ORCID-id: 0000-0001-5471-551X
Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM. (CeLeKT)ORCID-id: 0000-0002-6937-345X
Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
2012 (Engelska)Ingår i: Seventh IEEE International Conference on Wireless, Mobile and Ubiquitous Technology in Education: Takamatsu, Kagawa, Japan, 27-30 March 2012, IEEE, 2012, s. 162-166Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Through the analysis of the different iterations of the Geometry Mobile (GEM) project, a mobile learning effort in the field of mathematics, we have identified a major architectural issue to be addressed in the design and implementation of m-learning applications. Due to the dynamic nature of the field many challenging requirements are continuously emerging. One of them relates to the possibility to support collaborative activities that demand sharing resources between students and their mobile devices in constantly changing conditions. These situations generate the need of using decentralized distributed architectures in which mobile devices can share resources to carry out the activity covering the concerns defined by the different stakeholders. This paper describes our current efforts connected to identifying a set of requirements for M-Learning activities. Thereafter, we elaborate on why a decentralized distributed system (DDS) can be used to provide a novel solution to tackle the mentioned above problems. Moreover, initial aspects related to the design of a DDS, including a self-adaptation mechanism are presented.

Ort, förlag, år, upplaga, sidor
IEEE, 2012. s. 162-166
Nyckelord [en]
mobile learning, self-adaptation, decentralized distributed system
Nationell ämneskategori
Datorsystem Mediateknik Interaktionsteknik
Forskningsämne
Data- och informationsvetenskap, Medieteknik
Identifikatorer
URN: urn:nbn:se:lnu:diva-16404DOI: 10.1109/WMUTE.2012.37Scopus ID: 2-s2.0-84860808453ISBN: 978-1-4673-0884-7 (tryckt)OAI: oai:DiVA.org:lnu-16404DiVA, id: diva2:477470
Konferens
IEEE Seventh International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, (WMUTE), Takamatsu, 27-30 March, 2012
Projekt
AMULETSTillgänglig från: 2012-01-13 Skapad: 2011-12-28 Senast uppdaterad: 2018-04-26Bibliografiskt granskad
Ingår i avhandling
1. Uncertainties in Mobile Learning applications: Software Architecture Challenges
Öppna denna publikation i ny flik eller fönster >>Uncertainties in Mobile Learning applications: Software Architecture Challenges
2012 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

The presence of computer technologies in our daily life is growing by leaps and bounds. One of the recent trends is the use of mobile technologies and cloud services for supporting everyday tasks and the sharing of information between users. The field of education is not absent from these developments and many organizations are adopting Information and Communication Technologies (ICT) in various ways for supporting teaching and learning. The field of Mobile Learning (M-Learning) offers new opportunities for carrying out collaborative educational activities in a variety of settings and situations. The use of mobile technologies for enhancing collaboration provides new opportunities but at the same time new challenges emerge.

One of those challenges is discussed in this thesis and it con- cerns with uncertainties related to the dynamic aspects that characterized outdoor M-Learning activities. The existence of these uncertainties force software developers to make assumptions in their developments. However, these uncertainties are the cause of risks that may affect the required outcomes for M-Learning activities. Mitigations mechanisms can be developed and included to reduce the risks’ impact during the different phases of development. However, uncertainties which are present at runtime require adaptation mechanisms to mitigate the resulting risks.

This thesis analyzes the current state of the art in self-adaptation in Technology-Enhanced Learning (TEL) and M-Learning. The results of an extensive literature survey in the field and the outcomes of the Geometry Mobile (GEM) research project are reported. A list of uncertainties in collaborative M-Learning activities and the associated risks that threaten the critical QoS outcomes for collaboration are identified and discussed. A detailed elaboration addressing mitigation mechanisms to cope with these problems is elaborated and presented. The results of these efforts provide valuable insights and the basis towards the design of a multi-agent self-adaptive architecture for multiple concerns that is illustrated with a prototype implementation. The proposed conceptual architecture is an initial cornerstone towards the creation of a decentralized distributed self-adaptive system for multiple concerns to guarantee collaboration in M-Learning. 

Ort, förlag, år, upplaga, sidor
Växjö, Sweden: Linnaeus University, 2012. s. 136
Nyckelord
distributed systems, uncertainties, self-adaptation, QoS, collaboration, M-Learning, TEL, Mobile Learning, Distributed Systems, Uncertainties, Quality of Service, Self-Adaptation
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:lnu:diva-18547 (URN)
Presentation
2012-03-12, Homeros, Linnaeus University, Växjö, 10:20 (Engelska)
Opponent
Handledare
Tillgänglig från: 2012-05-09 Skapad: 2012-05-04 Senast uppdaterad: 2018-01-12Bibliografiskt granskad

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