• 한국컴퓨터정보학회논문지
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• 제13권4호
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• pp.127-132
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• 2008

무선 센서 네트워크 기술은 빠르게 발전하고 있으며, 다양한 산업 분야에서 적용이 가능하다. 무선 센서 네트워크는 그 특성상 한 번 배포되면 배터리의 교환이 어렵기 때문에 에너지를 효율적으로 사용하도록 설계되는 것이 매우 중요하다. 이러한 목적을 달성하기 위해 에너지 효율적인 라우팅 프로토콜에 대한 많은 연구가 진행되고 있다. 센서 네트워크에서 에너지 소비는 전송거리와 보내고자 하는 데이터에 비례한다. LEACH-C와 같은 클러스터 기반라우팅 기법들은 센서 노드들의 클러스터링을 통하여 데이터 전달 거리를 최소화시킴으로서 에너지의 효율성을 얻는다. 하지만 LEACH-C에서는 클러스터링을 구성할 때 클러스터 구성 노드들의 거리 총합만을 고려한다. 본 논문에서는 에너지 사용에 큰 영향을 미치는 기지국과 클러스터 헤드간의 거리를 고려한 클러스터 헤드 선택 알고리즘을 제안한다. 제안 방법은 LEACH-C에 비해 기지국의 위치가 일정 거리 이상 떨어져 있을 경우평균$4{\sim}7%$의 성능 향상 결과를 제공하였다. 이 결과는 클러스터 기반 라우팅 알고리즘에서 클러스터 헤드와 기지국간의 거리를 고려하는 것이 라이프타임 성능 측면에 영향을 미칠 수 있음을 보여 주었다.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.55-64
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• 2023

The Internet of Things (IoT) is the combination of the internet and various sensing devices. IoT security has increasingly attracted extensive attention. However, significant losses appears due to malicious attacks. Therefore, intrusion detection, which detects malicious attacks and their behaviors in IoT devices plays a crucial role in IoT security. The intrusion detection system, namely IDS should be executed efficiently by conducting classification and efficient feature extraction techniques. To effectively perform Intrusion detection in IoT applications, a novel method based on a Conventional Neural Network (CNN) for classification and an improved Genetic Algorithm (GA) for extraction is proposed and implemented. Existing issues like failing to detect the few attacks from smaller samples are focused, and hence the proposed novel CNN is applied to detect almost all attacks from small to large samples. For that purpose, the feature selection is essential. Thus, the genetic algorithm is improved to identify the best fitness values to perform accurate feature selection. To evaluate the performance, the NSL-KDDCUP dataset is used, and two datasets such as KDDTEST²¹ and KDDTEST⁺ are chosen. The performance and results are compared and analyzed with other existing models. The experimental results show that the proposed algorithm has superior intrusion detection rates to existing models, where the accuracy and true positive rate improve and the false positive rate decrease. In addition, the proposed algorithm indicates better performance on KDDTEST⁺ than KDDTEST²¹ because there are few attacks from minor samples in KDDTEST⁺. Therefore, the results demonstrate that the novel proposed CNN with the improved GA can identify almost every intrusion.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.431-433
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• 2016

본 논문에서는 Delay Tolerant Network(DTN) 환경에서 메시지 분포를 사용하여 효율적인 중계노드를 선택하는 기법을 제안한다. DTN은 종단 간 연결이 불확실한 네트워크에서의 통신을 Store-Carry-Forward 방식을 사용하여 메시지를 목적 노드에 전달한다. 또한 종단 간 연결이 불확실한 상황에서도 중계 노드를 통해 메시지를 목적 노드에 전달하여 높은 전송률을 보장한다. 하지만 에피데믹(Epidemic) 라우팅이나 Spray and Wait 라우팅과 같은 기존 다중 복사 라우팅 알고리즘은 접촉한 모든 노드에게 메시지를 복사하여 메시지 복사로 인한 오버헤드가 높아진다. 반면에 PRoPHET 라우팅과 같은 단일 복사 알고리즘은 적은 오버헤드를 발생시키지만 중계 노드 수 감소로 인한 메시지 전송률 감소 현상이 나타난다. 본 논문에서 제안하는 알고리즘은 기존 DTN 라우팅의 문제점을 보완하기 위해 네트워크의 메시지 분포를 분석하여 효율적인 중계 노드를 선택할 수 있는 확률을 결정한다. 본 논문에서는 모의실험을 통해 제안하는 알고리즘이 기존 DTN 라우팅 알고리즘과 비교하여 더 효율적임을 증명한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2894-2909
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• 2015

As the number of mobile devices such as smart phones and tablets explodes, the need for new services or applications is also rapidly increasing. Smart class application is one of the emerging applications, in which most of contents are distributed to all members of a class simultaneously. It is highly required to select relay nodes to cover shadow area of radio as well as extend coverage, but existing algorithms in a smart class environment suffer from high control packet overhead and delay for exchanging topology information among all pairs of nodes to select relay nodes. In addition, the relay selection procedure should be repeated in order to adapt to the dynamic topology changes caused by link status changes or device's movement. This paper proposes the learning based relay selection algorithm to overcome aforementioned problems. The key idea is that every node keeps track of its relay quality in a fully distributed manner, where RQI (Relay Quality Indicator) is newly defined to measure both the ability of receiving packets from content source and the ability of successfully relaying them to successors. The RQI of each node is updated whenever it receives or relays broadcast packet, and the node having the higher RQI is selected as a relay node in a distributed and run-time manner. Thus, the proposed algorithm not only removes the overhead for obtaining prior knowledge to select relay nodes, but also provides the adaptability to the dynamic topology changes. The network simulation and experimental results prove that the proposed algorithm provides efficient and reliable content distribution to all members in a smart class as well adaptability against network dynamics.

• 산업경영시스템학회지
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• 제26권4호
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• pp.23-30
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• 2003

This study develops an efficient heuristic which is based on genetic approach for AGVs flow path layout problem. The suggested solution approach uses a algorithm to replace two 0-1 integer programming models and a branch-and-bound search algorithm. Genetic algorithms are a class of heuristic and optimization techniques that imitate the natural selection and evolutionary process. The solution is to determine the flow direction of line in network AGVs. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. Genetic algorithm procedure is suggested, and a simple illustrative example is shown to explain the procedure.

• ETRI Journal
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• 제37권4호
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• pp.717-726
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• 2015

In this paper, we study an asymmetric two-way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time-division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy-efficient transmission. Our scheme is based on the asymmetric level of the two source nodes' target signal-to-noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.

• 한국콘텐츠학회논문지
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• 제9권8호
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• pp.49-56
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• 2009

본 논문에서는 무선 ad-hoc 네트워크에서 보다 효율적인 라우팅을 위해 기존의 에너지, 연결강도와 이력 정보를 추가하는 CDS 구성 방법을 제안한다. 무선 ad-hoc 네트워크에서는 CDS(connected dominating set)를 구성할 때 보다 빠르고 간단하며 효율적인 전력 소모 관리가 가능한 알고리즘이 필요하다. CDS로 결정된 노드는 그렇지 않은 노드에 비해 통신량이 많기 때문에 CDS는 최소화 되어야 하며 지속적인 위치 이동이 이루어지지 않는 무선 ad-hoc 네트워크에서는 가장 효율적연 CDS를 결정하고 망 구성이 이루어진 후 가급적 재구성 되지 않아야 한다. 이 문제점들을 개선하고자 기존에 제안된 EL + ND 기반 CDS 구성법보다 효율적인 EL + ND + Sel 기반 CDS 구성법을 제안하고 실험을 통하여 성능을 비교 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1077-1093
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• 2013

This paper proposes a new network coordinator node design to select the most suitable wireless technology for WBANs by using fuzzy logic. Its goal is to select a wireless communication technology available considering the user/application requirements and network conditions. A WBAN is composed of a set of sensors placed in, on, or around human body, which monitors the human body functions and the surrounding environment. In an effort to send sensor readings from human body to medical center or a station, a WBAN needs to stay connected to a local or a wide area network by using various wireless communication technologies. Nowadays, several wireless networking technologies may be utilized in WLANs and/or WANs each of which is capable of sending WBAN sensor readings to the desired destination. Therefore, choosing the best serving wireless communications technology has critical importance to provide quality of service support and cost efficient connections for WBAN users. In this work, we have developed, modeled, and simulated some networking scenarios utilizing our fuzzy logic-based NCN by using OPNET and MATLAB. Besides, we have compared our proposed fuzzy logic based algorithm with widely used RSSI-based AP selection algorithm. The results obtained from the simulations show that the proposed approach provides appropriate outcomes for both the WBAN users and the overall network.

• Journal of Communications and Networks
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• 제8권1호
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• pp.116-122
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• 2006

Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.79-88
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• 2024

The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.