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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Ambient I...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Ambient Intelligence and Humanized Computing
Article . 2018 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
DBLP
Article
Data sources: DBLP
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Implementation and performance evaluation of two fuzzy-based systems for selection of IoT devices in opportunistic networks

Authors: Miralda Cuka; Donald Elmazi; Kevin Bylykbashi; Evjola Spaho; Makoto Ikeda; Leonard Barolli;

Implementation and performance evaluation of two fuzzy-based systems for selection of IoT devices in opportunistic networks

Abstract

The opportunistic networks are a subclass of delay-tolerant networks where communication opportunities (contacts) are intermittent and there is no need to establish an end-to-end link between the communication nodes. The internet of things (IoT) present the notion of large networks of connected devices, sharing data about their environments and creating a diverse ecosystem of sensors, actuators, and computing nodes. IoT networks are a departure from traditional enterprise networks in terms of their scale and consist of heterogeneous collections of resource constrained nodes that closely interact with their environment. There are different issues for these networks. One of them is the selection of IoT devices in order to carry out a task in opportunistic networks. In this work, we implement and compare two fuzzy-based systems (FBS1 and FBS2) for IoT device selection in opportunistic networks. For FBS1, we use three input parameters: IoT device storage (IDST), IoT device waiting time (IDWT) and IoT device remaining energy (IDRE). The output parameter is IoT device selection decision (IDSD). For FBS2, we consider four input parameters adding IoT device security (IDSC) as a new parameter. Comparing complexity of FBS1 and FBS2, the FBS2 is more complex than FBS1. But, the FBS2 is more flexible and makes a better selection of IoT devices than FBS1.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    Top 10%
Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Top 10%