• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.69-76
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• 2022

The traveling salesman problem(TSP) is one of the most famous combinatorial optimization problem. So far, many metaheuristic search algorithms have been proposed to solve the problem, and one of them is local search. One of the very important factors in local search is neighbor generation method, and random-based neighbor generation methods such as inversion have been mainly used. This paper proposes 4 new greedy-based neighbor generation methods. Three of them are based on greedy insertion heuristic which insert selected cities one by one into the current best position. The other one is based on greedy rotation. The proposed methods are applied to first-choice hill-climbing search and simulated annealing which are representative local search algorithms. Through the experiment, we confirmed that the proposed greedy-based methods outperform the existing random-based methods. In addition, we confirmed that some greedy-based methods are superior to the existing local search methods.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.59-67
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• 2009

In wireless sensor networks (WSNs), geographic greedy forwarding fails to move a packet further towards its destination if the sender does not have any closer node to the destination in its one hop transmission region. In this paper, we propose a enhanced geographic routing, called CGR(Cost based Geographic Routing) for efficient data delivery against void problem environment. CGR first establishes Shadow Bound Region and then accomplishes Renewing Cost Function Algorithm for effective greedy forwarding data delivery. Our simulation results show significant improvements compared with existing schemes in terms of routing path length, success delivery ratio and energy efficiency.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.52-59
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• 2007

This paper presents a greedy method for user-steered mesh segmentation, which is based on the merging priority metric defined for representing the geometric properties of meaningful parts. The priority metric is a weighted function composed of five geometric parameters: distribution of Gaussian map, boundary path concavity, boundary path length, cardinality, and segmentation resolution. This scheme can be extended without any modification only by defining more geometric parameters and adding them. Our experimental results show that the shapes of segmented parts can be controlled by setting up the weight values of geometric parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1075-1082
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• 2008

A greedy forwarding algorithm is one of the most suitable solutions for routing in vehicular ad-hoc networks. Compared to conventional routing protocols for mobile ad-hoc networks, greedy forwarding based routing protocols maintain only local information of neighbors instead of per-destination routing entries, and thus they show better performance in highly-mobile vehicular ad-hoc networks. With greedy forwarding, each node learns its geographical position and periodically broadcasts a beacon message including its position information. Based on the position information, each node selects a neighbor node located closest to the destination node as the next forwarder. One of the most serious problems in greedy forwarding is the lost link problem due to the mobility of nodes. In this paper, we propose a new algorithm to reduce the lost link problem. The proposed algorithm aims to find an efficient and stable routing path by taking account of the position of neighbors and the last beacon reception time. Our simulation results show that the proposed algorithm outperforms the legacy greedy algorithm and its variants.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.459-468
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• 2008

A data stream which is a massive unbounded sequence of data elements continuously generated at a rapid rate. Many recent research activities for emerging applications often need to deal with the data stream. Such applications can be web click monitoring, sensor data processing, network traffic analysis. telephone records and multi-media data. For this. data processing over a data stream are not performed on the stored data but performed the newly updated data with pre-registered queries, and then return a result immediately or periodically. Recently, many studies are focused on dealing with a data stream more than a stored data set. Especially. there are many researches to optimize continuous queries in order to perform them efficiently. This paper proposes a query optimization algorithm to manage continuous query which has multiple join operators(Multi-way join) over data streams. It is called by an Extended Greedy query optimization based on a greedy algorithm. It defines a join cost by a required operation to compute a join and an operation to process a result and then stores all information for computing join cost and join cost in the statistics catalog. To overcome a weak point of greedy algorithm which has poor performance, the algorithm selects the set of operators with a small lay, instead of operator with the smallest cost. The set is influenced the accuracy and execution time of the algorithm and can be controlled adaptively by two user-defined values. Experiment results illustrate the performance of the EGA algorithm in various stream environments.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.715-726
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• 2006

Web service technologies provide a standard means for interoperation and integration of heterogeneous applications distributed over the Internet. For efficient execution of hierarchically interacting composite web services, this paper proposes an approach to distribute web service invocations over peer systems effectively, exploiting intensional XML data embedding external service calls as a result of well services. A cost-based optimization problem on the execution of web services using intensional results was formalized, and a heuristic search method to find an optimal solution and a greedy algorithm to generate an efficient invocation plan quickly were suggested in this paper. Experimental evaluation shows that the proposed greedy algorithm provides near-optimal solutions in an acceptable time even for a large number of Web services.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.29-39
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• 2008

Greedy routing which is easy to apply to geographic wireless sensor networks is frequently used. Greedy routing works well in dense networks whereas in sparse networks it may fail. When greedy routing fails, it needs a recovery algorithm to get out of the communication void. However, additional recovery algorithm causes problems that increase both the amount of packet transmission and energy consumption. Communication void is a condition where all neighbor nodes are further away from the destination than the node currently holding a packet and it therefore cannot forward a packet using greedy forwarding. Therefore we propose a VODUA(Virtually Ordered Distance Upgrade Algorithm) as a novel idea to improve and solve the problem of void. In VODUA, nodes exchange routing graphs that indicate information of connection among the nodes and if there exist a stuck node that cannot forward packets, it is terminated using Distance Cost(DC). In this study, we indicate that packets reach successfully their destination while avoiding void through upgrading of DC. We designed the VODUA algorithm to find valid routes through faster delivery and less energy consumption without requirement for an additional recovery algorithm. Moreover, by using VODUA, a network can be adapted rapidly to node's failure or topological change. This is because the algorithm utilizes information of single hop instead of topological information of entire network. Simulation results show that VODUA can deliver packets from source node to destination with shorter time and less hops than other pre-existing algorithms like GPSR and DUA.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.11
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• pp.19-24
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• 2007

This paper presents a performance analysis of dynamic channel allocation (DCA) based on the greedy approach (GA) for orthogonal frequency division multiple access (OFDMA) systems over Rayleigh fading channels. The GA-based DCA achieves its performance improvement using multi-user diversity. We analyze the statistics of the number of allocable users (NAU), which represents the multi-user diversity order at each allocation process. The derived statistics are then used to analyze the performance of GA-based DCA. The analysis results show that the number of subcarriers allocated to each user must be equal to achieve the maximum system performance (i.e., based on outage probability and data throughput).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.6
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• pp.485-491
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• 2013

Recently, with the proliferation of social network services, users and many companies hope that their information spread more faster. In order to study the information diffusion in the social networks, many algorithms such as greedy algorithm and heuristic algorithm have been proposed. However, the greedy algorithm is too complicated to use in real-life social network, and the heuristic algorithms have been studied under the uniform distribution of diffusion probability, which is different from the real social network property. In this paper, we propose an heuristic information diffusion maximization algorithm based on diffusion probability and node degree. For performance evaluation, we use real social network database, and it is verified that our proposed algorithm activates more active nodes than existing algorithms, which enables faster and wider information diffusion.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.429-434
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• 2003

본 논문은 작업일정계획에서 부하평준화 문제를 효율적으로 해결하기 위하여 tabu 탐색을 적용함에 있어서 확률적 선별에 기반하여 이웃해를 생성하는 방법을 제시한다. 이웃해 생성은 부하평준화를 위해 일정을 조정할 대상 작업을 선택하는 단계와 선택된 작업에 대해 일정 조정의 방향을 결정하는 단계로 구분된다. 확률적 선별에 기반한 이웃해 생성은 우선 무작위로 추출된 작업에 대해서 탐색의 질을 개선시킬 수 있는 가능성에 대한 추정치에 따라 확률을 부여하고, 이 확률에 기반하여 선택여부를 결정함으로써 이웃해를 선별하는 방법이다. 실제 현장의 부하평준화 문제를 대상으로 이웃해 생성 방법으로 무작위 방법, 그리디(greedy) 방법과의 비교 실험을 통해 확률적 선별에 기반한 이웃해 생성 방법의 성능을 검증하였다.