M
Makoto Ikeda
Researcher at Fukuoka Institute of Technology
Publications - 422
Citations - 3687
Makoto Ikeda is an academic researcher from Fukuoka Institute of Technology. The author has contributed to research in topics: Optimized Link State Routing Protocol & Node (networking). The author has an hindex of 30, co-authored 385 publications receiving 3225 citations. Previous affiliations of Makoto Ikeda include Oxford Brookes University & Seikei University.
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Journal ArticleDOI
Implementation of Intelligent Hybrid Systems for Node Placement Problem in WMNs Considering Particle Swarm Optimization, Hill Climbing and Simulated Annealing
TL;DR: Two intelligent hybrid systems are implemented:PSO and HC based system called WMN-PSOHC and PSO and SA based systemcalled WMn-PSOSA, both of which have better performance than WMN -PSO.
Proceedings ArticleDOI
Performance Analysis of OLSR and BATMAN Protocols Considering Link Quality Parameter
TL;DR: The implementation and analysis of the testbed considering the Link Quality Window Size (LQWS) parameter of Optimized Link State Routing (OLSR) and Better Approach To Mobile Ad-hoc Networking (B.T.A.M.N.) protocols found that throughput of TCP was improved by reducing LQWS.
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Trustworthiness in P2P: performance behaviour of two fuzzy-based systems for JXTA-overlay platform
TL;DR: The simulation results show that the proposed two fuzzy-based trustworthiness system for P2P communication in JXTA-overlay have a good behaviour and can be used successfully to evaluate the reliability of the new peer connected in J XTA- overlay.
Journal ArticleDOI
Performance evaluation of a QoS-aware fuzzy-based CAC for LAN access
TL;DR: This paper proposes and implements a fuzzy-based admission control system (FACS) and carried out many simulations to evaluate the performance of the proposed system, showing that the system has a good performance.
Journal ArticleDOI
A comparison study of Hill Climbing, Simulated Annealing and Genetic Algorithm for node placement problem in WMNs
TL;DR: This work compares Hill Climbing, Simulated Annealing and Genetic Algorithm by simulations for node placement problem to find the optimal distribution of router nodes in order to provide the best network connectivity and provide thebest coverage in a set of randomly distributed clients.