• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.771-773
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• 2005

There have been researches about analyzing the information retrieval patterns of log file to efficiently obtain the users' information research patters in web environment. The methods frequently used in their researches is to suggest the algorithms by which the frequent one is derived from the path traversal patterns in efficient way. But one of their general problems is not to provide the proper solution in case of complex, that is, general topological patterns. Therefore this paper tries to suggest a efficient algorithm after defining the general information retrieval pattern.

• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.395-402
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• 2007

Wireless sensor networks have many sensor nodes which response sudden events in a sensor fields. Some efficient routing protocol is required in a sensor networks with mobile sink node. A data-path template is offered for the data announcement and data request from source node and sink node respectively. Sensed data are transferred from source node to sink node using short-distance calculation. Typical protocols for the wireless networks with mobile sink are TTDD(Two-Tier Data Dissemination) and CBPER(Cluster-Based Power-Efficient Routing). The porposed SPDR(Short-Path Data Routing) protocol in this paper shows more improved energy efficiencies from the result of simulations than the typical protocols.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.25-36
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• 2009

In this paper, we propose an efficient data management scheme for path queries and containment queries which are occurred frequently. The proposed data management scheme considers a change of the containment of products during a transport and supports a path of changed products by representing a path of various containments. Also, the compression utilizing the structure of supply chain reduces the stored data volumes. As a result, our method outperforms the existing methods in terms of storage efficiency and query processing time.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.296-305
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• 2000

Virtual wavelength path (VWP) is the optical path when a wavelength conversion is possible in a wavelength division multiplexing (WDM) network that is transmission infrastructure for the next generation high speed backbone networks. To achieve efficient design for VWP networks, we must consider VWP routing, wavelength assignment, and wavelength conversion while satisfying many technical constraints of the WDM networks. In this study we propose an integrated model for efficient VWP design in WDM networks. We also develope a 3-phase algorithm, each of which deals with routing, wavelength assignment and route and wavelength reassignment, respectively. In our computational experiments, phase 1 algorithm can solve the problem to the optimality for medium size test networks. Phase 2 algorithm is an efficient heuristic based on a reduced layered network and can give us an effective wavelength assignment. Finally, phase 3 algorithm reconfigure VWP routing and its wavelength assignment to concentrate wavelength conversion nodes in the suggested VWP network.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Journal of Ocean Engineering and Technology
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• v.20 no.1 s.68
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• pp.69-76
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• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.782-791
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• 2005

In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the Path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the Nosed navigational algorithm for autonomous mobile robots.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.295-299
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• 2005

In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.

• Journal of KIISE
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• v.44 no.7
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• pp.710-718
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• 2017

As graphs are becoming increasingly large, the costs for storing and managing data are increasing continuously. Shortest path discovery over a large graph requires long running time due to frequent disk I/Os and high complexity of the graph data. Recently, graph summarization techniques have been studied, which reduce the size of graph data and disk I/Os by representing highly dense subgraphs as a single super-node. Decompressing should be minimized for efficient shortest path discovery over the summarized graph. In this paper, we analyze the decompression performance of a summarized graph and propose an approximate technique that discovers the shortest path quickly with a minimum error ratio. We also propose an exact technique that efficiently discovered the shortest path by exploiting an index built on paths containing super-nodes. In our experiments, we showed that the proposed technique based on the summarized graph can reduce the running time by up to 70% compared with the existing techniques performed on the original graph.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1390-1411
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• 2024

Underwater Wireless Sensors Networks (UWSNs) are deployed in remotely monitored environment such as water level monitoring, ocean current identification, oil detection, habitat monitoring and numerous military applications. Providing scalable and efficient routing is very challenging in UWSNs due to the harsh underwater environment. The biggest difficulties are the nodes inherent movement due to water current, long delay in data transmission, low bandwidth of the acoustic signal, high error rate and energy scarcity in battery powered nodes. Many routing protocols have been proposed to solve the aforementioned problems. There are three broad categories of routing protocols namely depth based, energy based and vector-based routing. Vector Based Forwarding protocols perform routing through virtual pipeline by defining their radius which give proper direction to packets communication. We proposed a routing protocol termed as Path-Oriented Energy Scaled Expanded Vector Based Forwarding (PESEVBF). PESEVBF takes into account all parameters; holding time, the source nodes packets routing path and void holes creation on the second hop; PESEVBF not only considers the packet upward advancement but also focus on density of the forwarded nodes in terms of number of potential forwarding and suppressed nodes for path selection. Node selection in resultant holding time is based on minimum Path Factor (PF) value. Moreover, the suppressed node will be selected for packet forwarding to avoid the void holes occurrences on the second hop. Performance of PESEVBF is compared with other routing protocols using matrices such as energy consumption, packet delivery ratio, packets dropping ratio and duplicate packets creation indicating considerable performance improvement.