Kosuke Ozera

Implementation of Intelligent Hybrid Systems for Node Placement Problem in WMNs Considering Particle Swarm Optimization, Hill Climbing and Simulated Annealing

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system, called WMN-PSO. Also, we implemented a simulation system based on Hill Climbing (HC) and Simulated Annealing (SA) for solving node placement problem in WMNs, called WMN-HC and WMN-SA, respectively. In this paper, we implement two intelligent hybrid systems: PSO and HC based system called WMN-PSOHC and PSO and SA based system called WMN-PSOSA. Then we compare WMN-PSO with implemented intelligent hybrid systems by conducting simulations. Simulation results show that intelligent hybrid systems have better performance than WMN-PSO. Comparing intelligent hybrid systems, the WMN-PSOHC converges faster than WMN-PSOSA.

Design and Implementation of a Hybrid Intelligent System Based on Particle Swarm Optimization and Distributed Genetic Algorithm

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system, called WMN-PSO, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in WMNs. In this paper, we implement a hybrid simulation system based on PSO and distributed GA (DGA), called WMN-PSODGA. We evaluate WMN-PSODGA by computer simulations. The simulation results show that the WMN-PSODGA has good performance when the number of GA islands is 64.

Performance Evaluation of WMN-PSOSA Considering Four Different Replacement Methods

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on Simulated Annealing (SA) for solving node placement problem in WMNs, called WMN-SA. In this paper, we implement a hybrid simulation system based on PSO and SA, called WMN-PSOSA. We evaluate the performance of WMN-PSOSA by conducting computer simulations considering four different replacement methods. The simulation results show that LDIWM have better performance than CM, RIWM and LDVM replacement methods.

Performance Evaluation of WMNs by WMN-PSOSA Simulation System Considering Constriction and Linearly Decreasing Inertia Weight Methods

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on Simulated Annealing (SA) for solving node placement problem in WMNs, called WMN-SA. In this paper, we implement a hybrid simulation system based on PSO and SA, called WMN-PSOSA. We evaluate the performance of WMN-PSOSA by conducting computer simulations considering two replacement methods: Constriction Method (CM) and Linearly Decreasing Inertia Weight Method (LDIWM). Simulation results show that the LDIWM has better performance than CM.

Performance Evaluation of Intelligent Hybrid Systems for Node Placement in Wireless Mesh Networks: A Comparison Study of WMN-PSOHC and WMN-PSOSA.

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented two intelligent hybrid systems for solving node placement problem in WMNs: PSO and Hill Climbing (HC) based system, called WMN-PSOHC, and PSO and Simulated Annealing (SA) based system, called WMN-PSOSA. In this paper, we evaluate two hybrid simulation systems WMN-PSOHC and WMN-PSOSA. We compare WMN-PSOHC with WMN-PSOSA by conducting computer simulations.

Performance Evaluation of WMNs by WMN-PSOSA Simulation System Considering Random Inertia Weight Method and Linearly Decreasing Vmax Method

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on Simulated Annealing (SA) for solving node placement problem in WMNs, called WMN-SA. In this paper, we implement a hybrid simulation system based on PSO and SA, called WMN-PSOSA. We evaluate the Performance of WMN-PSOSA by conducting computer simulations considering Random Inertia Weight Method (RIWM) and Linearly Decreasing Vmax Method (LDVM). The simulation results show that the LDVM has better performance than RIWM for this scenario.

A Fuzzy Approach for Secure Clustering in MANETs: Effects of Distance Parameter on System Performance

A Mobile Ad hoc Network (MANET) is a multihop wireless network in which the mobile nodes are dynamic in nature and has a limited bandwidth and minimum battery power. Due to this challenging environment the mobile nodes can be grouped into clusters to achieve better stability and scalability. Grouping the mobile nodes is called clustering, in which a leader node is elected to manage the entire network. In this paper, first we introduce various approaches for clustering focused on different performance metrics. Then, we show some clustering schemes such as Mobility-based clustering, Energy-efficient clustering, Connectivity-based clustering, Weighted-based clustering. Finally, we present and compare two Fuzzy based systems (called F2SMC1 and F2SMC2) for improving the security of cluster nodes in MANETs. We compare the performance of F2SMC1 and F2SMC2 and show that the F2SMC2 is more complex than F2SMC1, but the F2SMC2 can manage the nodes in the cluster better than F2SMC1.

Performance Evaluation of WMN-PSOHC and WMN-PSO Simulation Systems for Node Placement in Wireless Mesh Networks: A Comparison Study

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on Hill Climbing (HC) for solving node placement problem in WMNs, called WMN-HC. In this paper, we implement a hybrid simulation system based on PSO and HC, called WMN-PSOHC. We compare WMN-PSO with WMN-PSOHC by conducting computer simulations. The simulation results show that the WMN-PSOHC has better performance than WMN-PSO.

Implementation of a WLAN Triage Testbed Using Fuzzy Logic: Evaluation for Different Number of Clients

Many devices communicate over Wireless Local Area Networks (WLANs). The IEEE 802.11e standard for WLANs is an important extension of the IEEE 802.11 standard focusing on QoS that works with any PHY implementation. The IEEE 802.11e standard introduces EDCF and HCCA. Both these schemes are useful for QoS provisioning to support delay-sensitive voice and video applications. EDCF uses the contention window to differentiate high priority and low priority services. However, it does not consider the priority of users. In this paper, in order to deal with this problem, we propose a Fuzzy-based Admission Control System (FACS). We implemented a triage testbed using FACS and carried out an experiment. The experimental results show that the number of connected clients is increased during Avoid phase, but does not change during Monitoring phase.

A Testbed for Admission Control in WLANs: Effects of RSSI on Connection Keep-Alive Time

Many devices communicate over Wireless Local Area Networks (WLANs). The IEEE 802.11e standard for WLANs is an important extension of the IEEE 802.11 standard focusing on QoS that works with any PHY implementation. The IEEE 802.11e standard introduces EDCF and HCCA. Both these schemes are useful for QoS provisioning to support delay-sensitive voice and video applications. EDCF uses the contention window to differentiate high priority and low priority services. However, it does not consider the priority of users. In this paper, in order to deal with this problem, we propose a Fuzzy-based Admission Control System (FACS). We implemented a testbed using FACS and carried out an experiment. The experimental results show that the connection keep alive time becomes longer, when the RSSI is increased. Also, the user request succsess ratio and connected time ratio are increased when the RSSI is increased.