A Survey on Controller Placement Algorithms for IoT Networks in Smart City Environments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0199636" target="_blank" >RIV/00216305:26220/26:0199636 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/11050873" target="_blank" >https://ieeexplore.ieee.org/document/11050873</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/AIEEE66149.2025.11050873" target="_blank" >10.1109/AIEEE66149.2025.11050873</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Survey on Controller Placement Algorithms for IoT Networks in Smart City Environments

Popis výsledku v původním jazyce

The Internet of Things (IoT) is transforming cities into smart cities by improving efficiency, safety, and sustainability through real-time data collection, analysis and decision making. A main challenge in IoT network is the Controller Placement Problem (CPP), which is essential for minimize latency, balance load, ensure reliability, and optimize energy consumption. This paper reviews 10 algorithms and approaches that have been proposed to solve CPP. To solve the CPP, algorithms minimize latency, improve fault tolerance, balance load, enhance energy efficiency, and ensure scalability. Various algorithms have been proposed to tackle these challenges, each algorithm has unique advantages. Among these algorithms the Hybrid Differential Evolution and Whale Optimization (DEWO) algorithm minimizes latency, improves fault tolerance and balance load. It achieved up to 20.25% performance improvement as compared to PSO in Deutsche topology. For energy efficiency, the Fitness Averaged-Rider Optimization Algorithm (FA-ROA) improves cluster head selection in WSN-IoT networks. It achieved up to 50% better energy efficiency as compared to other algorithms. Other approaches such as GWOAP, Louvain Algorithm with Betweenness-Centrality, CPCSA and Tabu Search Algorithm have also been analyzed for CPP. This review paper provides a detailed analysis of these approaches and algorithms in addressing the complexities of controller placement in IoT networks. By exploring these algorithms this review paper aim to contribute to the development of more efficient, reliable, and scalable smart city infrastructure.

Název v anglickém jazyce

A Survey on Controller Placement Algorithms for IoT Networks in Smart City Environments

Popis výsledku anglicky

The Internet of Things (IoT) is transforming cities into smart cities by improving efficiency, safety, and sustainability through real-time data collection, analysis and decision making. A main challenge in IoT network is the Controller Placement Problem (CPP), which is essential for minimize latency, balance load, ensure reliability, and optimize energy consumption. This paper reviews 10 algorithms and approaches that have been proposed to solve CPP. To solve the CPP, algorithms minimize latency, improve fault tolerance, balance load, enhance energy efficiency, and ensure scalability. Various algorithms have been proposed to tackle these challenges, each algorithm has unique advantages. Among these algorithms the Hybrid Differential Evolution and Whale Optimization (DEWO) algorithm minimizes latency, improves fault tolerance and balance load. It achieved up to 20.25% performance improvement as compared to PSO in Deutsche topology. For energy efficiency, the Fitness Averaged-Rider Optimization Algorithm (FA-ROA) improves cluster head selection in WSN-IoT networks. It achieved up to 50% better energy efficiency as compared to other algorithms. Other approaches such as GWOAP, Louvain Algorithm with Betweenness-Centrality, CPCSA and Tabu Search Algorithm have also been analyzed for CPP. This review paper provides a detailed analysis of these approaches and algorithms in addressing the complexities of controller placement in IoT networks. By exploring these algorithms this review paper aim to contribute to the development of more efficient, reliable, and scalable smart city infrastructure.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IEEE Workshop on Advances in Information Electronic and Electrical Engineering

ISBN

978-1-6654-6562-5

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

IEEE

Místo vydání

NEW YORK

Místo konání akce

Vilnius, Lithuania

Datum konání akce

15. 5. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001548087800030