Driver mental status plays a crucial role in ensuring road safety and factors such as fatigue, stress, and lack of attention significantly increase the risk of accidents. Conventional monitoring systems often rely on single indicators, which may not provide a comprehensive evaluation of driver condition. In this study, we propose a Fuzzy Logic (FL) based system for assessing driver condition by integrating multiple parameters, including physical parameters for deciding Driver Body Condition (DBC). We call this system FL-based DBC (FLDBC) system. As input parameters for FLDBC system we consider Pupil Dilation (PD), Driver Facial Expression Changes (DFEC), Handle Reaction Time (HRT) and Driver Heart Rate Status (DHRS). The output parameter is DCB. We evaluated the implemented system by computer simulations. The simulation results show that DCB is good when the pupil dilation is normal. With increasing HRT, the DCB value increased. Also, when DFEC and HRT changed, the DCB value increased.

DOI： 10.1007/978-3-032-10347-5_20

Scopus

Wireless Mesh Networks (WMNs) are well-known for their exceptional resilience and rapid deployment capabilities, making them well-suited for a diverse range of networking applications. However, these networks face several challenges, including congestion, interference, diminished data transfer rates, packet loss, and increased latency. The strategic placement of mesh routers is critical for mitigating these issues. Nevertheless, determining the optimal locations for mesh routers within WMNs is a complex problem that is classified as NP-hard. To solve this problem, we propose and implement an intelligent simulation system based on Cuckoo Search (CS) algorithm, called WMN-CS. This study evaluates the performance of WMNs utilizing the WMN-CS system considering load balancing among mesh routers and Exponential distribution of mesh clients. The simulation results demonstrate that the system effectively facilitates load balancing while improving connectivity and user coverage.

DOI： 10.1007/978-3-032-05772-3_9

Scopus

Wireless Mesh Networks (WMNs) are recognized as good and diverse networking applications due to their robustness and rapid deployment potential. Nevertheless, these networks have challenges such as congestion, interference, reduced throughput, packet loss, and increased latency. The optimal placement of mesh routers plays a pivotal role in mitigating these issues. However, identifying the optimal router locations is computationally intractable and is considered an NP-hard problem. To solve this problem, we propose and implement an intelligent simulation framework based on Cuckoo Search (CS) algorithm named WMN-CS. This study evaluates the performance of WMNs using the WMN-CS system considering load balancing among mesh routers measured by Load Difference (LD) metric and a middle scale WMN. Simulation results demonstrate that the proposed system minimize the LD while maintaining good network connectivity and client coverage.

DOI： 10.1007/978-3-032-10344-4_5

Scopus

Wireless Mesh Networks (WMNs) are rapidly developing due to their usefulness and deployment capabilities, making them effective solutions for diverse networking applications. However, these networks face several challenges, including congestion, interference, diminished data transfer rates, packet loss, and increased latency. The strategic placement of mesh routers is crucial for mitigating these issues. However, finding the best placement of mesh routers in WMNs is a complex and challenging issue and is classified as an NP-hard problem. To solve this problem, we propose and implement a Cat Swarm Optimization (CSO) based intelligent simulation system, called WMN-CSO. We evaluate the performance of proposed system for Uniform distribution of mesh clients considering different Mixture Ratios (MRs). The simulation results indicate that the system performs better for smaller MR values.

DOI： 10.1007/978-3-032-10347-5_21

Scopus

Wireless Mesh Networks (WMNs) are knowing for their significant robustness and rapid deployment capabilities, rendering them effective solutions for wireless networking. However, these networks face several challenges, including congestion, interference, diminished data transfer rates, packet loss, and increased latency. The strategic placement of mesh routers is crucial in mitigating these issues. Nevertheless, determining the optimal locations for mesh routers in WMNs is a challenge and is classified as an NP-hard problem. To solve this issue, we propose and implement an intelligent simulation system that employs Cuckoo Search (CS) algorithm, called WMN-CS system. In this study, we evaluate the performance of a WMN utilizing WMN-CS system considering the replacement parameter. We conducted computer simulations to evaluate the proposed system considering Size of Giant Component (SGC) and Number of Covered Mesh Clients (NCMC) metrics. The evaluation results indicate that WMN-CS can achieve the maximum value of SGC across all tested replacement parameters. On the other hand, the performance of WMN-CS for NCMC varies depending on the specific replacement parameter utilized. The findings suggest that a smaller replacement parameter performs better in the considered scenarios.

DOI： 10.1007/978-3-031-96099-4_19

Scopus

For safe driving and decrasing the risk of traffic accidents, it is important to control the driver mental status. In this paper, we implement an intelligent system based on Fuzzy Logic (FL) for deciding Driver Mental Status (DMS). We call this system FL-based DMS System (FLDMSS). The input parameters for FLDMSS are Driver Anxiety Level (DAL), Traffic Situation (TS) and Driving Operating Time (DOT). The output parameter is DMS. We evaluated the implemented system by computer simulations. The simulation results show that DMS is very good when the driving operating time is short. With increasing of DAL and DOT values, the DMS value is decreased. But when TS is good, the DMS value is increased.

DOI： 10.1007/978-3-031-76452-3_34

Scopus

Wireless Mesh Networks (WMNs) are known for their significant resilience and rapid deployment capabilities, rendering them effective solutions for various networking applications. However, these networks face several challenges, including congestion, interference, diminished data transfer rates, packet loss, and increased latency. The strategic placement of mesh routers is crucial for mitigating these issues. However, to find the best locations for mesh routers in WMNs is a complex challenge because it is classified as an NP-hard problem. To tackle this challenge, we propose and implement a Cuckoo Search (CS) algorithm based intelligent simulation system, called WMN-CS. In this study, we evaluate the performance of WMN using WMN-CS system considering the load balancing among mesh routers. The simulation results demonstrate that the system effectively manages load balancing while maximizing connectivity and user coverage.

DOI： 10.1007/978-3-031-96093-2_19

Scopus

Network slicing is a key enabling technology for 5G/B5G networks, allowing diverse services with distinct requirements to coexist on shared infrastructure. However, ensuring the trustworthiness of slices and improving performance, reliability, and security remains a significant challenge. This paper proposes a Hierarchical Fuzzy Trust System (H-FTS) to evaluate the trustworthiness of network slices. The system integrates Quality of Service (QoS) metrics (Latency, PLR, Throughput), Slice Failure Rate (SFR), Security Posture (SP), and Isolation Integrity (II). A lower-level Type-1 Fuzzy Logic System (T1 FLS) assesses the QoS score. This score, along with SFR, SP and II, is fed into an upper-level Interval Type-2 FLS (IT2 FLS) to compute Slice Trust (ST) score. Simulation results demonstrate the effectiveness of H-FTS, indicating that improvements in QoS, SP, and II have a positive impact on ST, while SFR shows a negative influence. The proposed H-FTS offers an interpretable and structured approach to trust assessment, essential for managing complex network slicing ecosystems.

DOI： 10.1007/978-3-031-96099-4_22

Scopus

The rapid advancement of wireless communication technology has had a significant impact on modern society, bringing about revolutionary changes in our daily lives and means of communication. In particular, introducing 5G and Beyond 5G (5G/B5G) networks is expected to expand communication coverage, including in the sky, at sea, and in outer space, while enabling ultra-low power consumption and low-cost communication. In order to adapt to such developments, Network Slicing (NS) is a technology that virtually divides the communication infrastructure to optimally allocate resources tailored to the requirements of individual services. Also, it is important to select slices that match the characteristics of each service. In B5G networks, individually optimized slices are required to support a wider variety of services and applications. To ensure that resources are distributed effectively without compromising the performance of any slice, in this paper, we propose a Fuzzy-based System for Selection of Slice Service Type (F3ST), which considers four parameters: Bandwidth (Bt), Latency (La), Connection Density (CD) and Slice Ability for Mobility Management (SAMM), which is a new parameter. From simulation results, we found that when Bt and SAMN are increased, the Slice Service Type Decision (SSTD) value is increased, but when La and CD are increased, the SSTD is decreased.

DOI： 10.1007/978-3-031-96093-2_17

Scopus

In P2P systems, especially in mobile P2P, it is necessary to consider the mobility tolerance of nodes and the instability of the network. The goal of this research is to develop a system for selecting reliable and best peers in a P2P communication environment. Previous research has focused on improving the reliability of peers and evaluating the reliability of the network as a whole. In this study, we focused on the reliability evaluation of each peer by using correlation coefficients and ns-3 simulator. Foe evaluation, we consider three parameters: delay time, packet loss and throughput. The simulation results show that the proposed systems can choose the best reliable peers.

DOI： 10.1007/978-3-031-46970-1_22

Scopus

Wireless Mesh Networks (WMNs) are effective networks because they have high-robustness and rapid deployment capabilities. However, they have have some issues such as congestion, interference, diminished data transfer speeds, packet losses, and increased latency. The location of mesh routers is one of the most critical decisions to deal with these problems. However, determining the optimal location of mesh routers in WMNs is difficult task and it is known to be an NP-hard problem. In order to solve this problem, we propose and implement an intelligent simulation system based on Cuckoo Search (CS) algorithm, which is a meta-heuristic approach. In this work, we evaluate the performance of WMN-CS system considering Normal, Stadium, Subway and Uniform distributions of mesh clients. The simulation results show that the distribution of mesh clients affects the performance of WMN-CS. The Normal distribution achieves a faster convergence compared to the other distributions. Comparing Stadium and Subway distributions, the Stadium distribution converges faster than the Subway distribution. The Uniform distribution shows the slowest convergence speed and has the lowest NCMC values.

DOI： 10.1007/978-3-031-72322-3_3

Scopus

DOI： 10.1007/978-3-031-64766-6_26

Scopus

Other Link： https://dblp.uni-trier.de/db/conf/imis/imis2024.html#LiuSB24

Wireless Mesh Networks (WMNs) are effective networks because they have high-robustness and rapid deployment capabilities. However, they have some issues such as congestion, interference, diminished data transfer speeds, packet losses, and increased latency. The location of mesh routers is one of the most critical decisions to deal with these problems. However, determining the optimal location of mesh routers in WMNs is difficult task and it is known to be an NP-hard problem. In order to solve this problem, we propose and implement an intelligent simulation system based on Cuckoo Search (CS) algorithm, which is a meta-heuristic approach. In this work, we assess the performance of WMN-CS considering Uniform, Weibull and Chi-square distributions of mesh clients. For evaluation, we carried out computer simulations. The simulation results show that the distribution of mesh clients affects the performance of WMN-CS. In case of Uniform distribution of mesh clients, the convergence speed is faster than the Weibull and Chi-square distributions, but the converged value of NCMC is the lowest among these three distributions. In the case of Weibull distribution, the convergence speed is slower than the Uniform and Chi-square distributions, but the converged value of NCMC is the highest among three of them. The performance of WMN-CS for Chi-square distribution is between Uniform and Weibull distributions.

DOI： 10.1007/978-3-031-70011-8_12

Scopus

DOI： 10.1007/978-3-031-57840-3_16

Scopus

Other Link： https://dblp.uni-trier.de/db/conf/aina/aina2024-1.html#SakamotoBL024