• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.22-27
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• 2020

Content centric networking (CCN) is regarded as promising internet architecture because it can provide network efficiency in terms of bandwidth consumption by separating contents from a specific network location and decrease network congestion events. However, the application of a CCN does not widely consider the side effects of mobile devices, particularly mobile content sources. For content source mobility, a full routing update is required. Therefore, in this study, a route optimization scheme is proposed for mobile content sources in a CCN environment to provide low communication overhead, short download time, and low resource consumption. The proposed scheme establishes a direct path between content requesters and a mobile content source for the exchange of interest and data packets using interest-piggybacked data packets. Based on the inherent CCN naming characteristics, the content source does not know the name prefix of the content consumer, and thus the proposed optimized CCN scheme utilizes the content router in the home domain of the content source.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4451-4466
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• 2014

We present joint radio selection and relay scheme that delivers data from a source to a sink in heterogeneous stationary sensor networks consisting of various radio interfaces. The proposed scheme finds the optimal relay nodes and their corresponding radio interfaces that minimize energy consumption throughout the network while satisfying the end-to-end packet deadline requirement. We formulate the problem of routing through radio interface selection into binary integer programs, and obtain the optimal solution by solving with an optimization solver. We examine a trade-off relationship between energy consumption and packet delay based on network level simulations. We show that given the end-to-end deadline requirement, our routing algorithm finds the most energy-efficient routing path and radio interface across mesh hops. We demonstrate that the proposed routing scheme exploits the given packet delivery time to turn into network benefit of reducing energy consumption compared to routing based on single radio interface.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.124-133
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• 2022

With the development of hardware technology and the advancement of numerical model methods, more precise weather forecasts can be carried out. In this paper, we propose a Unicon Optimization scheme combining Loop Vectorization, Dependency Vectorization, and Code Modernization to optimize and increase Maintainability the Unicon source contained in SCAM, a simplified version of CESM, and present an overall SCAM structure. This paper tested the unicorn optimization scheme in the SCAM structure, and compared to the existing source code, the loop vectorization resulted in a performance improvement of 3.086% and the dependency vectorization of 0.4572%. And in the case of Unicorn Optimization, which applied all of these, the performance improvement was 3.457% compared to the existing source code. This proves that the Unicorn Optimization technique proposed in this paper provides excellent performance.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.169.1-169.1
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• 2005

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.119-131
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• 2009

Existing proposals on route optimization for nested Network Mobility(NEMO) have a problem that it is difficult to optimize a route promptly in an environment where a MR moves frequently. Also, they have L3 handoff latency as well as route optimization latency until an optimized route is formed. In this paper, we propose a L3 handoff scheme that supports fast route optimization for nested NEMO without any additional optimization procedure. To achieve this, our proposed scheme is designed to include a procedure that an AR acquires address informations of a MR. After receiving binding update message from the MR, the AR performs the binding update procedure with the MR's HA on behalf of the MR. Packets are delivered to the AR only passing by the MR's HA after a bi-directional tunnel is formed between the AR and the HA. The result of our performance evaluation has shown that the proposed scheme could provide excellent performance compared with the RRH and the ONEMO.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3037-3054
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• 2013

Interference between primary user (PU) and secondary user (SU) transceivers should be mitigated in order to implement underlay spectrum sharing in cognitive radio networks (CRN). Considering this scenario, an improved joint subcarrier and bit allocation scheme for cognitive user with primary users' cooperation (PU Coop) in CRN is proposed. In this scheme, the optimization problem is formulated to minimize the average interference power level at the PU receiver via PU Coop, which guarantees a higher primary signal to interference plus noise ratio (SINR) while maintaining the secondary user total rate constraint. The joint optimal scheme is separated into subcarrier allocation and bit assignment in each subcarrier via arith-metric geo-metric (AM-GM) inequality with asymptotical optimization solution. Moreover, the joint subcarrier and bit optimization scheme, which is evaluated by the available SU subcarriers and the allocated bits, is analyzed in the proposed PU Coop model. The performance of cognitive spectral efficiency and the average interference power level are investigated. Numerical analysis indicates that the SU's spectral efficiency increases significantly compared with the PU non-cooperation scenario. Moreover, the interference power level decreases dramatically for the proposed scheme compared with the traditional Hughes-Hartogs bit allocation scheme.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• Korean Journal of Computational Design and Engineering
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• v.15 no.1
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• pp.24-32
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• 2010

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.87-95
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• 2010

In this paper, we propose an improved TDoA (Time Difference of Arrival) localization scheme using PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: re-estimation of TDoA parameters and re-localization of a tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. The simulation results show that the proposed scheme achieves a more superior location performance to the traditional TDoA localization in both LoS (Line-of-Sight) and NLoS (Non-Line-of-Sight) channel environments.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.337-342
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• 2007

A multi-objective optimization technique was implemented to obtain optimal topologies of the inner reinforcement for a vehicle's hood simultaneously considering the static stiffness of bending and torsion and natural frequency. In addition, a smoothing scheme was used to suppress the checkerboard patterns in the ESO method. Two models with different curvature were chosen in order to investigate the effect of curvature on the static stiffness and natural frequency of the inner reinforcement. A scale factor was employed to properly reflect the effect of each objective function. From several combinations of weighting factors, a Pareto-optimal topology solution was obtained. As the weighting factor for the elastic strain efficiency went from 1 to 0, the optimal topologies transmitted from the optimal topology of a static stiffness problem to that of a natural frequency problem. It was also found that the higher curvature model had a larger static stiffness and natural frequency than the lower curvature model. From the results, it is concluded that the ESO method with a smoothing scheme was effectively applied to topology optimization of the inner reinforcement of a vehicle's hood.