• Journal of Communications and Networks
• /
• 제17권3호
• /
• pp.306-320
• /
• 2015

Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 춘계학술대회 논문집
• /
• pp.516-520
• /
• 1996

This paper focues on development of a timer selection algorithm for IEEE802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. Therefore, the object of this paper is to develop timer selection algorithm to minimize a certain penalty function. This paper presents an algorithm based on Genetic Algorithm. The efficacy of the algorithm has been demonstrated by a series of simulation experiments.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.772-776
• /
• 2004

This paper proposes an interference avoidance approach for Constraint-Based Routing (CBR) algorithm in the Multi-Protocol Label Switching (MPLS) network. The MPLS network itself has a capability of integrating among any layer-3 protocols and any layer-2 protocols of the OSI model. It is based on the label switching technology, which is fast and flexible switching technique using pre-defined Label Switching Paths (LSPs). The MPLS network is a solution for the Traffic Engineering(TE), Quality of Service (QoS), Virtual Private Network (VPN), and Constraint-Based Routing (CBR) issues. According to the MPLS CBR, routing performance requirements are capability for on-line routing, high network throughput, high network utilization, high network scalability, fast rerouting performance, low percentage of call-setup request blocking, and low calculation complexity. There are many previously proposed algorithms such as minimum hop (MH) algorithm, widest shortest path (WSP) algorithm, and minimum interference routing algorithm (MIRA). The MIRA algorithm is currently seemed to be the best solution for the MPLS routing problem in case of selecting a path with minimum interference level. It achieves lower call-setup request blocking, lower interference level, higher network utilization and higher network throughput. However, it suffers from routing calculation complexity which makes it difficult to real task implementation. In this paper, there are three objectives for routing algorithm design, which are minimizing interference levels with other source-destination node pairs, minimizing resource usage by selecting a minimum hop path first, and reducing calculation complexity. The proposed CBR algorithm is based on power factor calculation of total amount of possible path per link and the residual bandwidth in the network. A path with high power factor should be considered as minimum interference path and should be selected for path setup. With the proposed algorithm, all of the three objectives are attained and the approach of selection of a high power factor path could minimize interference level among all source-destination node pairs. The approach of selection of a shortest path from many equal power factor paths approach could minimize the usage of network resource. Then the network has higher resource reservation for future call-setup request. Moreover, the calculation of possible path per link (or interference level indicator) is run only whenever the network topology has been changed. Hence, this approach could reduce routing calculation complexity. The simulation results show that the proposed algorithm has good performance over high network utilization, low call-setup blocking percentage and low routing computation complexity.

• Journal of Positioning, Navigation, and Timing
• /
• 제8권4호
• /
• pp.193-200
• /
• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• 한국통신학회논문지
• /
• 제38A권10호
• /
• pp.858-864
• /
• 2013

4세대 무선통신 환경에서, 가장 중요한 문제 중의 하나는 사용자들에게 적합한 접근 네트워크를 발견하고 선택하는 것이다. 본 논문에서는 그룹결정기법을 이용한 새로운 네트워크 선택 메커니즘을 제안하고, 이종 네트워크 환경에서 수직 핸드오버를 위한 네트워크 선택 기법에 따른 영향을 분석한다. 비슷한 QoS 요구조건들을 갖는 사용자들의 그룹들이 동시에 이용할 수 있는 네트워크를 탐색하며, 한 서비스 영역은 여러 특성을 갖는 다수의 접근 네트워크들이 존재하는 경우를 고려한다. 비슷한 특성을 갖는 네트워크들을 그룹으로 묶어, 일차적으로 그룹간의 판별을 통해 적합한 그룹을 선택한 후, 그 그룹에서 네트워크 선택 알고리즘에 의한 네트워크 순위를 통해 최적의 네트워크를 선택해 준다. 제안된 시스템을 MADM 기법 중 GRA, SAW 그리고 TOPSIS 방법으로 비교 및 평가하였다. MATLAB 시뮬레이션 결과, 제안된 알고리즘은 네트워크들의 특성과 사용자의 선호도에 따라 더욱 효과적인 선택을 할 수 있음을 알 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권11호
• /
• pp.5276-5298
• /
• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
• /
• pp.420-422
• /
• 2004

The non-ideal characteristics of wireless communication are found in sensor network. And sensor network must also address new raised issues. The efficient ad-hoc routing algorithm is considered the nice solution for new raised sensor network problems. To design this efficient ad-hoc routing algorithm, we study and evaluate new components in routing algorithm. Namely, new components are Link estimator, Neighbor table and Parent selection. We have tested this related experiment using the TIP-30C. TIP-30C is sensor network node that is designed by KETI(Korea Electronic Technology Institute).

• 대한지리학회지
• /
• 제40권4호
• /
• pp.441-453
• /
• 2005

본 연구의 목적은 지형자료에 대한 계층화 알고리즘을 개발하여 하계망을 일반화하고자 하였다. 하계망은 계층적인 구조를 갖기 때문에 일반화를 위해 선형사상들에 대한 지형자료의 계층화가 요구된다. 하계망 일반화의 절차는 하계망의 계층화, 차수별 선택과 제거, 그리고 알고리즘 적용으로 진행하였다. 계층화는 하계망의 고도에 따른 방향 결정, Stroke Segment 서열화. Strahler 차수화로 진행하였으며, 선형사상의 선택과 제거는 지리자료의 질의를 통해 차수와 선의 길이를 기준으로 처리하였다 개선된 Simoo 알고리즘은 선형사상의 곡률을 낮추고 완만화에 효과적이었다 연구결과는 공간적으로 다양한 계층구조를 갖는 사상들에 대한 일반화를 개선할 수 있을 것으로 기대된다.

• International Journal of Computer Science & Network Security
• /
• 제21권2호
• /
• pp.9-13
• /
• 2021

Type 2 diabetes mellitus (T2D) is a complex diabetes disease that is caused by high blood sugar, insulin resistance, and a relative lack of insulin. Many studies are trying to predict variant genes that causes this disease by using a sample disease model. In this paper we predict diabetic and normal persons by using fisher score feature selection, chi-2 feature selection and Logistic Regression supervised learning algorithm with best accuracy of 90.23%.

• Asian Pacific Journal of Cancer Prevention
• /
• 제15권23호
• /
• pp.10539-10542
• /
• 2015

A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps, firstly choosing the risk factors by combining two feature selection algorithms, then providing the predictive value by neural network. Based on the method framework, an algorithm LCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practical applications. The proposed method is suitable for health monitoring and self-testing. Experiments showed it can actually provide satisfactory accuracy under low dimensions of risk factors.