ABCDecision: A Simulation Platform for Access Selection Algorithms in Heterogeneous Wireless Networks

Haydar, Jamal; Ibrahim, Abbas; Samhat, Abed Ellatif; Pujolle, Guy

doi:10.1155/2010/787098

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Before any implementation, it is essential to choose the right location to place the LoRa gateways in order to communicate with LoRa nodes and receive the data all the way from Khaldeh campus to Wardanieh campus. Several Wi-Fi and radio frequency (rf) planning software tools and simulation Platforms already exist [21], [22]. For the simulation, we used HTZ communication software which is the ideal tool for planning homogeneous and heterogeneous wireless networks.…”

Section: Lora Coveragementioning

confidence: 99%

Intelligent Bus Application for Smart City based on LoRa Technology and RBF Neural Network

Kanaan

Haydar

Samaha

et al. 2020

Wseas Transactions on Systems and Control

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Nowadays smart transportation is one of the most important smart city applications for all the facilities it provides, as well, achieves green transportation. One of these applications include bus monitoring systems for schools and universities. This paper proposes an integrated bus tracking and monitoring system using Internet of Things (IoT) mainly LoRa technology for Islamic University of Lebanon (IUL) to ease the bus issue that comprises a barrier for good service. In the proposed system, we have implemented a case study to monitor the position, speed, humidity and temperature of IUL shuttle buses. In addition to the tracking, a prediction algorithm is implemented for computation of the arrival time of the bus to the Wardanieh campus. The estimation is based on artificial intelligence neural network mainly the Radial Basis Function (RBF) algorithms for the sake of finding the predicted time of arrival in different locations and scenarios starting from Khaldeh campus to the Wardanieh campus. The collected data are instantly shown on a user interface for monitoring, whereas the exact location and arrival time of the bus will be displayed on an android application for students. Results show that the arrival estimated time error is about 0.18%.

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Section: Lora Coveragementioning

confidence: 99%

Intelligent Bus Application for Smart City based on LoRa Technology and RBF Neural Network

Kanaan

Haydar

Samaha

et al. 2020

Wseas Transactions on Systems and Control

Self Cite

View full text Add to dashboard Cite

show abstract

“…(3) for CN ∈ CN do (4) for ∈ X do (5) = Fuzzy( ); (6) end for (7) end for (8) for ∈ S do (9) = Fuzzy( ); (10) end for (11) for ∈ S do (12) for CN ∈ CN do (13) Calcula t eSa t ; (14) Sa t * ⇒ Sd ; (15) end for (16) if ∀Sd ! = 0 then (17) Se lectCN with best value Sd ; (18) else if ∀Sd == 0 then (19) Se lectCN with best value of preferential attribute ; (20) end if (21) end for (22) end while…”

Section: Fuzzy Processingmentioning

confidence: 99%

“…It is responsible for selecting the best one from multiple coexistent wireless networks that have heterogeneous characteristics, to conform to the requirements of services. This selection principle is called always best connected (ABC) [4]. Due to the ABC principle of network selection, varieties of network selection methods using mathematical models have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy and Utility Based Network Selection for Heterogeneous Networks in High-Speed Railway

Yan

Dong

Zheng

et al. 2017

Wireless Communications and Mobile Computing

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Due to the complexity and fluctuation of the wireless network statuses in the high-speed railway scenario, the existing works of the network selection problem in heterogeneous wireless networks face two major challenges, that is, the imprecise statuses and mobility. In this paper, we propose FSNS, a novel dynamic imprecise-aware network selection approach to solve the problems. The imprecise statuses are inferred by fuzzy rules and the status-awareness feature of the status monitor module enables a dynamic network selection. Through the status monitor and fuzzy processing modules, FSNS is formulated as utility functions for meeting quality-of-service (QoS) requirements. What is more, we carry out plenty of simulation experiments and compare FSNS approach with an enhanced TOPSIS method and fuzzy MADM (FMADM) scheme through simulation experiments of two types of services. The results indicate that FSNS outperforms both TOPSIS and FMADM for a good performance improvement and a preferable decision to keep relative stability and reduce abnormal selections. The conclusion of experimental results has some extent pragmatic value since the network statuses of the simulation are complex and fluctuate by real-world data from high-speed railways.

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Fuzzy Multi-Attribute Utility Based Network Selection Approach for High-Speed Railway Scenario

Yan

Dong

Zheng

et al. 2017

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

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ABCDecision: A Simulation Platform for Access Selection Algorithms in Heterogeneous Wireless Networks

Cited by 3 publications

References 5 publications

Intelligent Bus Application for Smart City based on LoRa Technology and RBF Neural Network

Intelligent Bus Application for Smart City based on LoRa Technology and RBF Neural Network

Fuzzy and Utility Based Network Selection for Heterogeneous Networks in High-Speed Railway

Fuzzy Multi-Attribute Utility Based Network Selection Approach for High-Speed Railway Scenario

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