Multi-objective service composition optimization problem in IoT for agriculture 4.0

One of the most well-known names that has recently attained new heights and set a standard is Internet of Things (IoT). IoT aims to connect all physical devices in such a way that they are subject to human control over the Internet.The emergence of IoT in almost all the industries has redesigned the...

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Vydáno v:Computing Ročník 106; číslo 12; s. 4039 - 4056
Hlavní autoři: Sharma, Shalini, Pathak, Bhupendra Kumar, Kumar, Rajiv
Médium: Journal Article
Jazyk:angličtina
Vydáno: Vienna Springer Vienna 01.12.2024
Springer Nature B.V
Témata:
Agribusiness
Agriculture
Artificial Intelligence
Composition
Computer Appl. in Administrative Data Processing
Computer Communication Networks
Computer Science
Genetic algorithms
Information Systems Applications (incl.Internet)
Internet of Things
Multiple objective analysis
Optimization
Pareto optimum
Quality of service
Regualr Paper
Software Engineering
Workflow
Smart agriculture
Internet of things
NSGA-II
Quality of service
MOGA
Service composition
90B50
Optimization
ISSN:0010-485X, 1436-5057
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Popis
Shrnutí:One of the most well-known names that has recently attained new heights and set a standard is Internet of Things (IoT). IoT aims to connect all physical devices in such a way that they are subject to human control over the Internet.The emergence of IoT in almost all the industries has redesigned them including smart agriculture. In today’s world, the growth in agriculture sector is rapid, smarter and precise than ever. In case of IoT, the objects are termed as services, sometimes with similar functionalities but distinct quality of service parameters. As the user’s requirements are complex, a single service cannot fulfil them efficiently. So, service composition is the solution. These services known as atomic services, are represented as workflow, with each of them having distinct candidate composite services. Fulfilling these Quality of Service (QoS) constraints makes it a NP-hard problem which can’t be solved using traditional approaches. Hence, comes the concept of evolutionary approaches. In this paper one of the evolutionary approach- NSGA-II is used to optimize the production of apple by composing the various services, taking into account the cost and time as multi-objective problem to be solved. This is for the very first time that QoS aware service composition problem has been optimized in smart agriculture as found in the literature. Results are further compared with multi-objective genetic algorithm (MOGA) and it has been found that NSGA-II outperforms MOGA by generating well-proportioned pareto optimal solutions.
Bibliografie:ObjectType-Article-1
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content type line 14
ISSN:0010-485X
1436-5057
DOI:10.1007/s00607-024-01346-2