• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.733-736
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• 2010

VANET(Vehicular Ad-hoc Network)은 노드를 차량으로 가정하는 개념의 MANET(Mobile Ad-hoc Network)로서 노드의 빠른 이동으로 인해 급격한 토폴로지의 변화가 일어난다. 하지만 차량 노드의 이동은 도로 상에서 제한되어 있기 때문에 토폴로지에 대한 상대적인 예측 가능성을 가지고 있다. 이는 교통이 혼잡한 도로 환경에서 그리디 기법을 이용하여 다음 홉을 결정할 때 보다 높은 정확성을 제공할 수 있어 경유 노드의 수와 포워딩 실패를 최소화한다. 본 논문은 위기 정보와 운전 시스템 정보를 기반으로 하는 차량 간 통신 라우팅 최적화 기법을 제안하고 기존의 GPSR(Greedy Perimeter Stateless Routing) 기법과 SAR(Spatial Aware Routing) 기법과의 비교를 통해 효율성과 신뢰성의 향상을 증명하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.464-470
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• 2011

V2V (Vehicle-to-Vehicle) is a special kind of VANET (Vehicular Ad-hoc Network), which has high mobility and frequent topology changes and causes the link breakage problem. To resolve this problem, geographic routing protocols such as greedy forwarding are proposed. However, the greedy forwarding approach selects the node closest to the destination node as the transfer node within the transmission range so that it may cause many problems owing to many intersections and many changes in vehicular traffic in urban areas. The paper proposes a greedy perimeter urban routing (GPUR) algorithm considering the presence of 2-hop neighbor nodes and the road characteristics. Simulation results using ns-2 reveal that the proposed GPUR algorithm significantly reduces the routing error problem and the probability of local maximum than the existing routing protocols.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.483-488
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• 2016

In this paper, we propose a prototype-based classification learning by using the nearest-neighbor rule. The nearest-neighbor is applied to segment the class area of all the training data with hyperspheres, and a hypersphere must cover the data from the same class. The radius of a hypersphere is computed by the mid point of the two distances to the farthest same class point and the nearest other class point. And we transform the prototype selection problem into a set covering problem in order to determine the smallest set of prototypes that cover all the training data. The proposed prototype selection method is designed by a greedy algorithm and applicable to process a large-scale training set in parallel. The prediction rule is the nearest-neighbor rule and the new training data is the set of prototypes. In experiments, the generalization performance of the proposed method is superior to existing methods.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.21-28
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• 2015

In this paper, we propose a prototype-based classification learning by using the nearest-neighbor rule. The nearest-neighbor is applied to segment the class area of all the training data into spheres within which the data exist from the same class. Prototypes are the center of spheres and their radii are computed by the mid-point of the two distances to the farthest same class point and the nearest another class point. And we transform the prototype selection problem into a set covering problem in order to determine the smallest set of prototypes that include all the training data. The proposed prototype selection method is based on a greedy algorithm that is applicable to the training data per class. The complexity of the proposed method is not complicated and the possibility of its parallel implementation is high. The prototype-based classification learning takes up the set of prototypes and predicts the class of test data by the nearest neighbor rule. In experiments, the generalization performance of our prototype classifier is superior to those of the nearest neighbor, Bayes classifier, and another prototype classifier.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.49-51
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• 2005

데이터 스트림 환경에서는 빠르게 무한히 생성되는 데이터를 가능한 빠른 시간에 질의 조건의 충족 여부를 판단하는 것이 시스템의 성능에서 중요한 역할을 한다. 따라서 신속한 판단을 위해 다수의 데이터 스트림 시스템에서 개별 선택 조건을 처리하는 것보다는 속성으로 통합하여 그룹 처리하는 방식을 사용하고 있다. 그룹 필터 처리시에는 그룹 필터의 순서에 따라 큰 처리비용의 차이가 발생하는데 본 논문은 데이터스트림 환경에서 시스템이 처리해야 하는 다수의 연속질의의 선택조건을 그룹 처리할 때 그룹 필터 연산의 처리 비용을 최소화 하기 위한 순서를 결정하는 방법을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.724-726
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• 2005

메모리 관련 수행은 일반적으로, 임베디드 시스템에서의 전체 전력 소모에서 상당한 양을 차지하고 있으며, 임베디드 시스템에서 사용되는 메모리 중 상당수가 에너지 절약을 용이하도록 다중의 작동 모드(예: 액티브, 스탠바이, 냅, 파워다운) 기능을 지니고 있다. 본 논문에서는 메모리 접근 코드의 스케줄링이 전력 소모에 미치는 관계를 이용함으로서 메모리의 작동 모드를 최대한 활용하는 문제에 대한 해결책을 제시한다. 기존의 방법에서는 (1) 제한된 레지스터 조건을 만족함과 (2) 효율적인 메모리 접근 모드 (예: 페이지, 버스트 모드) 활용 등을 후반부의 별개 작업으로 고려한 반면, 본 제안한 방법은 (1)과 (2) 두 요소를 메모리 접근 코드 스케줄링에 긴밀히 결합시켜 전력 소모를 효과적으로 줄이고자 하였다. 벤치마크를 사용한 실험에서 우리가 제안한 방법을 사용하면, 기존의 일방적 우선순위를 기반으로 한 그리디 방식보다 평균 $32.13\%$ 더 적은 전력 소모를 가짐을 입증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.531-532
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• 2009

위치기반 라우팅 기법들은 소스에서 목적지노드로 데이터 패킷을 전송하기 위한 목적으로 널리 사용된다. 오리지널 그리디 포워딩 기법은 실제 무선링크의 신뢰성을 고려하지 않아 수많은 데이터 패킷 재전송이 발생한다. 이러한 문제를 해결하기 위해 PRR ${\times}$ Distance 기법이 제안되었지만 실제 무선링크의 비대칭성을 고려하지 않아 여전히 많은 재전송이 발생한다. 제안기법은 포워딩할 데이터 패킷을 가진 현재 노드의 전송 반경 내에서 전송 가능한 1-hop과 2-hop 라우팅 경로를 찾는다. 이들 라우팅 경로들 중 기대전송비용이 최소가 되는 경로를 선택하여 데이터와 ACK 패킷을 전송한다. 시뮬레이션을 결과를 통해 제안기법이 기존 기법들보다 높은 신뢰성과 에너지 효율을 가짐을 보인다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1151-1168
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• 2009

Improving packet loss does not necessarily coincide with the improvement in user perceivable QoS because each frame carries different degree of importance. We propose Significance-aware packet scheduling (SAPS) to maximize user perceivable QoS. SAPS carries out two fundamental issues of packet scheduling: "What to transmit" and "When to transmit?" To adapt to the available bandwidth, it is necessarily to transmit the subset of the data packets if the entire set of packets can not be transmitted. "Packet Significance" quantifies the importance of the frame by elaborately incorporating frames' dependency. Greedy approach is used in selecting packets and transmission schedule is determined based on the Packet Significance. The proposed scheme is tested using publicly available MPEG-4 video clips. Decoding engine is embedded in the simulation software and user perceivable QoS is exposeed in termstermiSNR. Throughout the simulation based experiment, the performance of the proposed scheme is compared two other schemes: Size-based packet scheduling and Bit-rate based best effort packet scheduling. SAPS successfully incorporates the semantics of a packet and improves user perceivable QoS significantly. It successfully provides unequal protection to more important packets.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.79-85
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• 2017

Vehicular ad-hoc networks (VANETs) cause link disconnection problems due to the rapid speed and the frequent moving direction change of vehicles. Link disconnection in vehicle-to-vehicle communication is an important issue that must be solved because it decreases the reliability of packet forwarding. From the characteristics of VANETs, greedy forwarding protocols using the position information based on the inter-vehicle distance have gained attention. However, greedy forwarding protocols do not perform well in the urban environment where the direction of the vehicle changes greatly. It is because greedy forwarding protocols select the neighbor vehicle that is closest to the destination vehicle as the next transmission vehicle. In this paper, we propose a greedy anycast forwarding (GAF) protocol to improve the reliability of the inter-vehicle communication. The proposed GAF protocol combines the greedy forwarding scheme and the anycast forwarding method. Simulation results show that the GAF protocol can provide a better packet delivery rate than existing greedy forwarding protocols.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2311-2319
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• 1999

We present two heuristic algorithms for the task allocation problem (NP-complete problem) in parallel computing. The problem is to find an optimal mapping of multiple communicating tasks of a parallel program onto the multiple processing nodes of a distributed-memory multicomputer. The purpose of mapping these tasks into the nodes of the target architecture is the minimization of parallel execution time without sacrificing solution quality. Many heuristic approaches have been employed to obtain satisfactory mapping. Our heuristics are based on genetic algorithms and simulated annealing. We formulate an objective function as a total computational cost for a mapping configuration, and evaluate the performance of our heuristic algorithms. We compare the quality of solutions and times derived by the random, greedy, genetic, and annealing algorithms. Our experimental findings from a simulation study of the allocation algorithms are presented.