Evaluation of Objective Function Descriptions And Optimization Methodologies For Task Allocation In A Dynamic Fog Environment

Industry, healthcare, and various other sectors are rapidly adopting the Internet of Things to drive information and automation systems. However, as the number of devices increases, the number of information sent over the network increases as well, inducing network congestion and a potential latency...

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Bibliographic Details
Published in2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) pp. 1 - 8
Main Authors Eyckerman, Reinout, Mercelis, Siegfried, Marquez-Barja, Johann, Hellinckx, Peter
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.12.2020
Subjects
automation systems
Complexity theory
current network infrastructure
distributing software
dynamic fog environment
healthcare
Heuristic algorithms
Internet of Things
multiobjective distribution scenarios
network congestion
objective function descriptions
optimisation
optimization methodologies
problem complexity
Security
smart vehicles
Software
task allocation
Task analysis
Vehicle dynamics
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Summary:Industry, healthcare, and various other sectors are rapidly adopting the Internet of Things to drive information and automation systems. However, as the number of devices increases, the number of information sent over the network increases as well, inducing network congestion and a potential latency increase. To ensure that demanding applications, such as smart vehicles, are supported in the current network infrastructure, we provide a general methodology of distributing software from the cloud toward the edge, reducing multiple objectives such as latency. In this research we define several problems in multi-objective distribution scenarios, and compare several methodologies for defining and solving the problem. Additionally, we propose a method for decreasing the problem complexity, improving performance with only slightly reduced accuracy.
DOI:10.1109/IOTSMS52051.2020.9340219