• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.9A
• /
• pp.916-922
• /
• 2007

Wireless networks (WNs) are developed and applied widely in a lot of areas. Now, a new generation of wireless networks is coming, and that is Wireless Mesh Network (WMN). At present, there are not so many researches which deal on this area. Most researches are derived from Mobile Ad hoc Networks (MANET) and WNs. In WMNs, there are some applications that require real-time delivery. To guarantee this, rate control and congestion control are needed. This problem leads to optimization issue in transport layer. In this paper, we propose a mathematical model which is applied in rate and congestion control in WNMs. From this model, we optimize rate and congestion control in WMNs by maximizing network utility. The proposed algorithm is implemented in distributed way both in links and sources.

• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.2827-2829
• /
• 1999

Genetic algorithms were described as a method of solving large-scaled optimization problems with complex constraints. It has overcome their slowness, a major drawback of genetic algorithms using hardware implementation of genetic algorithm processor (GAP). In this study, we proposed GAP effectively connecting the goodness of survival-based GA, steady-state GA, tournament selection. Using Pipeline Parallel processing, handshaking protocol effectively, the proposed GAP exhibits 50% speed-up over survival-based GA which runs one million crossovers per second(1MHz). It will be used for high speed processing such of central processor of EHW, robot control and many optimization problem.

• FOCUS: LIFE SCIENCE
• /
• no.1
• /
• pp.9.1-9.5
• /
• 2024

Method development for complex low molecular mass (LMM) samples using reversed-phase (RP) separation conditions presents significant challenges due to the presence of many unknown analytes over wide concentration ranges. This guide aims to optimize method parameters-column length (L), temperature (T), flow rate (F), and final mobile phase conditions (Øfinal)-to maximize separation peak capacity. Validated by prior research, this protocol benefits laboratories dealing with metabolomics, natural products, and contaminant screening. This practical guide provides a structured approach to maximizing peak capacity for complex LMM separations. It complements computational optimization strategies and offers a step-by-step method development process. The Snyder-Dolan test is highlighted as essential for determining the need for gradient or isocratic elution and guiding column length decisions. The decision tree framework helps analysts prioritize variable optimization to develop effective separation methods for complex samples.

• Journal of KIISE
• /
• v.41 no.12
• /
• pp.1145-1151
• /
• 2014

In this paper, we propose MPLO(Multi-Path routing with Local Optimization) for load balancing in the tactical backbone network. The MPLO manages global metric and local metric separately. The global metric is propagated to other routers via a routing protocol and is used for configuring loop-free multi-path. The local metric reflecting link utilization is used to find an alternate path when congestion occurs. We verified MPLO could effectively distribute user traffic among available routers by simulation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.6
• /
• pp.1017-1024
• /
• 2010

Under the Kyoto Protocol many countries have been requested to participate in emissions trading with the assigned $CO_2$ emissions. In this environment, it is inevitable to change the system and market operation in deregulated power systems, and then ensuring safety margin is becoming more important for balancing system security, economy and $CO_2$ emissions. Nowadays, available transfer capability (ATC) is a key index of the remaining capability of a transmission system for future transactions. This paper presents a novel approach to the ATC evaluation with $CO_2$ emissions using multi-objective particle swarm optimization (MOPSO) technique. This technique evolves a multi-objective version of PSO by proposing redefinition of global best and local best individuals in multi-objective optimization domain. The optimal power flow (OPF) method using MOPSO is suggested to solve multi-objective functions including fuel cost and $CO_2$ emissions simultaneously. To show its efficiency and effectiveness, the results of the proposed method is comprehensively realized by a comparison with the ATC which is not including $CO_2$ emissions for the IEEE 30-bus system, and is found to be quite promising.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.3
• /
• pp.133-144
• /
• 2000

Genetic Algorithm(GA) has been known as a method of solving large-scaled optimization problems with complex constraints in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementations of Genetic Algorithm Processors(GAP) are focused on in recent studies. In this paper, a hardware-oriented GA was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuos generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm in simulation. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1㎒), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.2B
• /
• pp.82-89
• /
• 2008

Mobile IP is the basic solution to provide host mobility, whereas network mobility refers to the concept of collective mobility of a set of nodes. In a network mobility scenario, mobile networks can be nested in a hierarchical form. That situation is referred to a nested mobile network Nested mobile networks exhibit the pinball routing problem, which becomes worse in proportion to the number of nested levels in the hierarchy. In this paper, we propose a routing optimization scheme having backward compatibility to the basic network mobility protocol and concerning heterogeneity of nested mobile network, also we perform comparison and analysis of proposed schemes.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.2
• /
• pp.410-415
• /
• 2007

Recent advances in sensor network technology have open up challenges for its effective routing. Routing protocol receives most of the attention because routing protocols might differ depending on the application and network architecture. In the rapidly changing environment and dynamic nature of network formation efficient routing and energy consumption are very crucial. Sensor networks differ from the traditional networks in terms of energy consumption. Thus, data-centric technologies should be used to perform routing to yield an energy-efficient dissemination. By exploiting the advantages of both ant colony optimization techniques in network routing and the ability of data centric muting to organize data for delivery, our approach will cover features for building an efficient autonomous sensor network.

• 순환기질환의공학회:학술대회논문집
• /
• 2006.10a
• /
• pp.44-45
• /
• 2006

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06a
• /
• pp.200-201
• /
• 2010