• Journal of Industrial Technology
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• v.26 no.B
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• pp.191-198
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• 2006

In this paper, we focus on a question. Which is better between time-based location update method and movement-based location update method? Or, does any other method combining the two methods show better performance? For the question, we propose a hybrid location update scheme, which integrates the time-based and the movement-based methods. In the proposed scheme, a mobile terminal updates its location after n cell boundary crossing and a time interval of T, or the inverse. We derive an analytical solution for the performance of the hybrid scheme with exponential cell resident time. From the numerical analysis, we conclude that the movement-based method seems to have better performance than the time-based and hybrid methods, that is the optimal costs occur at T=0.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.141-147
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• 2007

In this paper, we define the multi-states exponential cell resident time mobility model for describing the mobility characteristics of mobile user and analyzed the total cost of the hybrid method using multi-states cell resident time. Generally, the mobile user has three states for its movement, such as staying, walking and driving. This multi-states cell resident time based hybrid method reflects the movement characteristics of mobile user and adapts the location update period according to the states of mobility speed. As a results of the performance analysis, we can get the optimum parameters of the hybrid method for multi-states based mobile users.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1309-1314
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• 2007

The assignment of cells to reporting or non-reporting cells is an NP-hard problem having an exponential complexity in the Reporting Cell Location Management (RCLM) system. Frequent location update may result in degradation of quality of service due to interference. Miss on the location of a mobile terminal will necessitate a search operation on the network when a call comes in. The number of reporting cells and which cell must be reporting cell should be determined to balance the registration (location update) and search (paging) operations to minimize the cost of RCLM system. T1is paper compares Max-Min ant system (MMAS), rank-based ant system (RAS) and hybrid method of MMAS and RAS that generally used to solve combinatorial optimization problems. Experimental results demonstrate that hybrid method of MMAS and RAS is an effective and competitive approach in fairly satisfactory results with respect to solution quality and execution time for the optimal design of location management system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.113-122
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• 2007

In this paper, we propose a multi-state based hybrid location update scheme, which integrates the time-based and the movement-based methods. In the proposed scheme, a mobile terminal updates its location after n cell boundary crossing and a time interval of T[sec]. We derive an analytical solution for the performance of the hybrid scheme with exponential cell resident time and evaluate it numerically with time-varying random walk mobility model, which we model as multi-states Markov chain. Furthermore, we also evaluate the scheme for arbitrary cell resident times by simulation. From the numerical analysis and the simulation results, we prove that the proposed scheme significantly outperforms the time-based and the movement-based methods, when implemented alone, more accurately adapting to the time-varying user mobility.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.757-766
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• 2007

Location services are used in mobile ad hoc and hybrid networks to locate either the geographic position of a given node in the network or a data item. One of the main usages of position location services is presented in location based routing algorithms. In particular, geographic routing protocols can route messages more efficiently to their destinations based on the destination node's geographic position, which is provided by a location service. In this paper, we propose an adaptive location service on the basis of fuzzy logic called FHLS (Fuzzy Hierarchical Location Service) for mobile ad hoc networks. The adaptive location update scheme using the fuzzy logic on the basis of the mobility and the call preference of mobile nodes is used by the FHLS. The performance of the FHLS is to be evaluated by a simulation, and compared with that of existing HLS scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.600-619
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• 2015

We propose a cost-efficient hybrid algorithm for online location updates that efficiently combines feature point detection with the online trajectory-based sampling algorithm. Our algorithm is designed to minimize the average trajectory error with the minimal number of sample points. The algorithm is composed of 3 steps. First, we choose corner points from the map as sample points because they will most likely cause fewer trajectory errors. By employing the online trajectory sampling algorithm as the second step, our algorithm detects several missing and important sample points to prevent unwanted trajectory errors. The final step improves cost efficiency by eliminating redundant sample points on straight paths. We evaluate the proposed algorithm with real GPS trajectory data for various bus routes and compare our algorithm with the existing one. Simulation results show that our algorithm decreases the average trajectory error 28% compared to the existing one. In terms of cost efficiency, simulation results show that our algorithm is 29% more cost efficient than the existing one with real GPS trajectory data.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.36.5-36
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• 2001

Localization is one of the key problems in the navigation of autonomous mobile robots. The probabilistic Markov localization approaches offer a good mathematical framework to deal with the uncertainty of environment and sensor readings but their use for realtime applications is limited by their computational complexity. This paper aims to reduce the high computational cost associated with the probabilistic Markov localization algorithm. We propose a hybrid landmark-based localization method combining triangulation and probabilistic approaches, which can efficiently update position probability grid, while the probabilistic framework allows to make use of any available sensor data to refine robot´s belief about its current location. The simulation results show the effectiveness and robustness of the method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.785-791
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• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1221-1230
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• 2004

In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.339-350
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• 2019

This research focuses on finite element model updating and damage assessment of structures at element level based on global nondestructive test results. For this purpose, an optimization system is generated to minimize the structural dynamic parameters discrepancies between numerical and experimental models. Objective functions are selected based on the square of Euclidean norm error of vibration frequencies and modal assurance criterion of mode shapes. In order to update the finite element model and detect local damages within the structural members, modern optimization techniques is implemented according to the evolutionary algorithms to meet the global optimized solution. Using a simulated numerical example, application of genetic algorithm (GA), particle swarm (PSO) and artificial bee colony (ABC) algorithms are investigated in FE model updating and damage detection problems to consider their accuracy and convergence characteristics. Then, a hybrid multi stage optimization method is presented merging advantages of PSO and ABC methods in finding damage location and extent. The efficiency of the methods have been examined using two simulated numerical examples, a laboratory dynamic test and a high-rise building field ambient vibration test results. The implemented evolutionary updating methods show successful results in accuracy and speed considering the incomplete and noisy experimental measured data.