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Journal of Edge Computing
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Journal of Edge Computing
Article . 2022
Data sources: DOAJ
DBLP
Article . 2022
Data sources: DBLP
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Graph theory methods for fog computing: A pseudo-random task graph model for evaluating mobile cloud, fog and edge computing systems

Authors: Andriy V. Ryabko; Oksana V. Zaika; Roman P. Kukharchuk; Tetiana A. Vakaliuk;

Graph theory methods for fog computing: A pseudo-random task graph model for evaluating mobile cloud, fog and edge computing systems

Abstract

The development and efficient application of Fog Computing technologies necessitate complex tasks associated with the management and processing of large data sets, including the creation of low-level networks that guarantee the functioning of end devices within the Internet of Things (IoT) concept. This article presents the utilization of graph theory techniques to address these issues. The proposed graph model enables the determination of fundamental characteristics of systems, networks, and network devices in Fog Computing, including optimal features and methods to maintain them in a functioning condition. This work demonstrates how to create and personalize graph displays by adding labels or highlighting to the graph nodes and edges of pseudo-random task graphs. The task graphs, described and visualized in Matlab code, represent the computational work to perform and data transfer between tasks, expressed in Megacycles per second and kilobits/kilobytes of data, respectively. The task graphs can be applied in both single-user systems, where one mobile device accesses a remote server, and multi-user systems, where many users access a remote server through a wireless channel. This set can be utilized by researchers to evaluate cloud/fog/edge computing systems and computational offloading algorithms.

Keywords

TK7885-7895, Computer engineering. Computer hardware, mobile cloud computing, graph theory, Electronic computers. Computer science, task graph model, computational offloading, QA75.5-76.95, fog computing, Internet of Things (IoT)

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selected citations
These citations are derived from selected sources.
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!
5
Top 10%
Average
Top 10%
gold