• Journal of Digital Convergence
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• v.10 no.4
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• pp.223-228
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• 2012

There are many algorithms to improve the network traffic and to avoid losing packets in the network. This paper proposed determining the shortest paths for hops, which are in the middle of the source and destination. The shortest path in this paper means the fastest path between them. Recently, dynamic routing algorithm is currently used now but this paper suggests the fastest paths between the source and the destination is by using the record of the network traffic history. People are using the networking and the network traffic is always corresponding to how many people use the networking in specific time. Therefore, I can predict the network condition by referring to the history of network traffic record, and then the shortest path can be produced without using RIP too much. It will be helpful to improve the network traffic.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.6
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• pp.230-237
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• 1985

Shortest path calculations for a large-scale network have to be performed using a decomposition techniqre, since the calculations require large memory size which increases by the square of the number of vertices in the network. Also, the calculation time increases by the cube of the number of vertices in the network. In the decomposition technique,the network is broken into a number of smaller size subnetworks for each of which shortest paths are computed. A union of the solutions provides the solution of the original network. In all of the decomposition algirithms developed up to now, boundary vertices which divide all the subnetworks have to be included in computing shortest paths for each subnetwork. In this paper, an improved algorithm is developed to reduce the number of boundary vertices to be engaged. In the algorithm, only those boundary vertices that are directly connected to the subnetwork are engaged. The algorithm is suitable for an application to real time computation using a parallel processor system which consists of a number of micro-computers or prcessors. The algorithm has been applied to a 39- vertex network and a 232-vertex network. The results show that it is efficient and has better performance than any other algorithms. A parallel processor system has been built employing an MZ-80 micro-computer and two Z-80 microprocessor kits. The former is used as a master processor and the latter as slave processors. The algorithm is embedded into the system and proven effective for real-time shortest path computations.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1778-1784
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• 2000

We consider the weighted shortest path updating problem, that is, the problem to reconstruct the weighted shortest paths in response to topology change of the network. This appear proposes a distributed algorithms that reconstructs the weighted shortest paths after several processors and links are added and deleted. its message complexity and ideal-time complexity are O(p$^2$+q+n') and O(p$^2$+q+n') respectively, where n' is the number of processors in the network after the topology change, q is the number of added links, and p is the total number of processors in he biconnected components (of the network before the topology change) including the deleted links or added links.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.677-685
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• 2009

There are a number of studies that propose transmission power control algorithms in wireless sensor networks. However, these algorithms have a lot of overhead in the initialization phase since a number of packets have to be transmitted to determine the optimal transmission power level. This paper proposes the transmission power control technique considering the shortest-path to minimize the hop-count without the occurrence of any power control messages. We applied the proposed technique on tree-based network component implemented on TinyOS. And we evaluated the performance including transmission energy and average network depth with 21 motes. Compared to before, the proposed technique reduces about 24.7% of the average electric current on transmitting. As a result of considering the shortest-path, the hop-count considering the shortest-path was about 41% less than a normal network.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.153-158
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• 1995

Finding shortest paths in networks is the fundamental problem in network theory and has numerous in Operations Research and related fields. The purpose of this study is to present a algorithm for solving the length of the shortest paths from a fixed node in a general network in which the arc distance can be arbitrary value. This algorithm has a worst computational bound of $n^3/4$ additions and $n^3/4$ comparisons, which is lower the worst computational bounds of other available algorithms.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.246-255
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• 2002

Constrained minimum Steiner tree (CMST) problem is a key issue in multicast routing with quality of service (QoS) support. Bounded shortest path algorithm (BSMA) has been recognized as one of the best algorithms for the CMST problem due to its excellent cost performance. This algorithm starts with a minimumdelay tree, and then iteratively uses a
-shortest-path (KSP) algorithm to search for a better path to replace a “superedge” in the existing tree, and consequently reduces the cost of the tree. The major drawback of BSMA is its high time complexity because of the use of the KSP algorithm. For this reason, we investigate in this paper the possibility of more efficient implementations of BSMA by using different methods to locate the target path for replacing a superedge. Our experimental results indicate that our methods can significantly reduce the time complexity of BSMA without deteriorating the cost performance.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.121-126
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• 2007

Among many graphs, directed acyclic graph(DAG) attracts many researchers due to its nice property of existence of topological sort. In some classic graph problems, it is known that, if we use the aforementioned property, then much efficient algorithms can be generated. So, in this paper, new algorithm for the all-pairs shortest path problem in a DAG is proposed. While the algorithm performing the iteration, it identifies the set of essential arcs which requires in a shortest path. So, the proposed algorithm has a running time of $O(m^*n+m)$, where m, n and $m^*$ denote the number of arcs, number of node, and the number of essential arcs in a DAG, respectively.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.451-457
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• 2012

Recently, as the use of real time traffic information of a car navigation system increases rapidly with the development of Intelligent Transportation Systems (ITS), path search is getting more important. Previous algorithms, however, are mostly for the shortest distance searching and provide route information using static distance and time information. Thus they could not provide the most optimal route at the moment which changes dynamically according to traffic. Accordingly, in this study, Semantic Shortest Path algorithm with Reduction ratio & Distance(SSP_RD) is proposed to solve this problem. Additionally, a routing model based on velocity reduction ratio and distance and a dynamic route link map are proposed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5B
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• pp.508-519
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• 2004

This paper proposed two multi-path constraint-based routing algorithms for Internet traffic engineering using MPLS. In normal constraint-based shortest path first (CSPF) routing algorithm, there is a high probability that it cannot find the required path through networks for a large bandwidth constraint that is one of the most important constraints for traffic engineering, The proposed algorithms can divide the bandwidth constraint into two or more sub-constraints and find a constrained path for each sub-constraint, if there is no single path satisfying the whole constraint. Extensive simulations show that they enhance the success probability of path setup and the utilization of network resources.