• Journal of KIISE:Databases
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• v.36 no.5
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• pp.405-410
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• 2009

This paper proposes an efficient path finding scheme capable of searching the paths to k static objects from a given query point, aiming at both improving the legacy k-nearest neighbor search and making it easily applicable to the road network environment. To the end of improving the speed of finding one-to-many paths, the modified A* obviates the duplicated part of node scans involved in the multiple executions of a one-to-one path finding algorithm. Additionally, the cost to the each object found in this step makes it possible to finalize the k objects according to the network distance from the candidate set as well as to order them by the path cost. Experiment results show that the proposed scheme has the accuracy of around 100% and improves the search speed by $1.3{\sim}3.0$ times of k-nearest neighbor searches, compared with INE, post-Dijkstra, and $na{\ddot{i}}ve$ method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.162-169
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• 2022

In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A^* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A^* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Korean Management Science Review
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• v.15 no.2
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• pp.229-237
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• 1998

This paper presents a new algorithm for the K Shortest Paths Problem which is developed with a Double Shortest Arborescence and an inward arc breaking method. A Double Shortest Arborescence is made from merging a forward shortest arborescence and a backward one with Dijkstra algorithm. and shows us information about each shorter path to traverse each arc. Then K shorter paths are selected in ascending order of the length of each short path to traverse each arc, and some paths of the K shorter paths need to be replaced with some hidden shorter paths in order to get the optimal paths. And if the cross nodes which have more than 2 inward arcs are found at least three times in K shorter path, the first inward arc of the shorter than the Kth shorter path, the exposed path replaces the Kth shorter path. This procedure is repeated until cross nodes are not found in K shorter paths, and then the K shortest paths problem is solved exactly. This algorithm are computed with complexity o($n^3$) and especially O($n^2$) in the case K=3.

• IE interfaces
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• v.24 no.4
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• pp.304-313
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• 2011

An Unmanned Aerial Vehicle(UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are currently employed in many military missions(surveillance, reconnaissance, communication relay, targeting, strike etc.) and a number of civilian applications(communication service, broadcast service, traffic control support, monitoring, measurement etc.). For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is the path planning to maximize survivability for UAV based on 3-dimensional environment. A mathematical programming model is suggested by using MRPP(Most Reliable Path Problem) and solved by transforming MRPP into SPP(Shortest Path Problem). This study also suggests a $A^*PS$ algorithm based on 3-dimensional environment to UAV's path planning. According to comparison result of the suggested algorithm and SPP algorithms (Dijkstra, $A^*$ algorithm), the suggested algorithm gives better solution than SPP algorithms.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.204-212
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• 2008

We study the routing problem in all-wireless networks based on cooperative transmissions. We model the minimum-energy cooperative path (MECP) problem and prove that this problem is NP-complete. We hence design an approximation algorithm called cooperative shortest path (CSP) algorithm that uses Dijkstra's algorithm as the basic building block and utilizes cooperative transmissions in the relaxation procedure. Compared with traditional non-cooperative shortest path algorithms, the CSP algorithm can achieve a higher energy saving and better balanced energy consumption among network nodes, especially when the network is in large scale. The nice features lead to a unique, scalable routing scheme that changes the high network density from the curse of congestion to the blessing of cooperative transmissions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.492-498
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• 2017

Subsea pipeline route design is a crucial task for the offshore oil and gas industry, and the route selected can significantly affect the success or failure of an offshore project. Thus, it is essential to design pipeline routes to be eco-friendly, economical and safe. Obstacle avoidance is one of the main problems that affect pipeline route selection. In this study, we propose a technique for designing an automatic obstacle avoidance. The Laplacian smoothing algorithm was used to make automatically generated pipeline routes fairer. The algorithms were fast and the method was shown to be effective and easy to use in a simple set of case studies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.8-14
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• 2002

This article presents a new algorithm for the K Shortest Paths Problem which develops initial K shortest paths, and repeal to expose hidden shortest paths with dual approach and to replace the longest path in the present K paths. The initial solution which comprises K shortest paths among shortest paths to traverse each arc is made from bidirectional Dijkstra algorithm. When a crossing node that have two or more inward arcs is found at least three time by turns in this K shortest paths, one inward arc of this crossing node, which has minimum detouring distance, is chosen, and a new path is exposed with joining a detouring subpath from source to this inward arc and a spur of a feasible path from this crossing node to sink. This algorithm, requires worst case time complexity of $O(Kn^2),\;and\;O(n^2)$ in the case $K{\leq}3$.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.199-205
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• 2011

This paper presents an algorithm capable of detecting free space for the autonomous vehicle navigation. The algorithm consists of two main steps: 1) estimation of longitudinal profile of road, 2) detection of free space. The estimation of longitudinal profile of road is detection of v-line in v-disparity image which is corresponded to road slope, using v-disparity image and hough transform, Dijkstra algorithm. To detect free space, we detect u-line in u-disparity image which is a boundary line between free space and obstacle's region, using u-disparity image and dynamic programming. Free space is decided by detected v-line and u-line. The proposed algorithm is proven to be successful through experiments under various traffic scenarios.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.11-18
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• 1983

This paper shows a new efficient solution method of finding an optimal path for a cruise missile or aircraft to a target which has the maximal survivability and penetration effectiveness against sophisticated defenses and over varied terrain. We first generate a grid structure over the terrain, to construct a network. Since our network usually has about 10,000 nodes, the conventional Dijkstra algorithm takes too much computational time in its searching process for a new permanent node. Our method utilizes the Hashing technique to reduce the computational time of the searching process. Extensive computational results are presented.