NDLI: An optimized Markov model to predict link quality in mobile wireless sensor networks

Content Provider	IEEE Xplore Digital Library
Author	de Araujo, G.M. Kaiser, J. Becker, L.B.
Copyright Year	2012
Description	Author affiliation: Department of Distributed Systems, Otto-Von-Guericke-Univesität Magdeburg, Germany (Kaiser, J.) \|\| Department of Automation and Control Systems, Federal University of Santa Catarina, Florianópolis, Brazil (de Araujo, G.M.; Becker, L.B.)
Abstract	Achieving RF connectivity is a critical issue in any wireless application. This is particularly challenging in mobile applications, as links are up and down many times. In such scenarios, where nodes keep on moving, it would be interesting for them to have knowledge of their remaining RF connectivity time. Such information can be used, for instance, to improve existing network protocols. The current paper addresses this problem by presenting the so-called Oriented Birth-Death (O-BD). The proposed solution is a modified version of the existing Birth-Death (BD) prediction model. We introduce in this work the notion of orientation to represent a tendency in the link future state. In other words, it considers if the link tends to increase or decrease the signal strength to make the prediction. Thereby a considerable prediction improvement is obtained, as shown in the evaluation performed. The proposed solution is well suited for mobile wireless sensor networks, whose nodes have low computational power and should be energy harvesting.
Starting Page	000307
Ending Page	000312
File Size	657396
Page Count	6
File Format	PDF
ISBN	9781467327121
ISSN	15301346
e-ISBN	9781467327138
e-ISBN	9781467327114
DOI	10.1109/ISCC.2012.6249313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-01
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Accuracy Markov processes Wireless sensor networks Production facilities History Mobile communication Connectivity prediction Mobility
Content Type	Text
Resource Type	Article
Subject	Signal Processing Mathematics Computer Networks and Communications Computer Science Applications Software

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