• Journal of Communications and Networks
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• 제17권4호
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• pp.384-393
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• 2015

This paper proposes an insect behavior-inspired routing algorithm for large-scale wireless mesh networks. The proposed algorithm is adapted from the behavior of an insect called Bombyx mori, a male silkmoth. Its unique behavior is its flying technique to find the source of pheromones. The algorithm consists of two steps: the shortest-path algorithm and the zigzag-path algorithm. First, the shortest-path algorithm is employed to transmit data. After half of the total hops, the zigzag-path algorithm, which is based on the movement of the male B. mori, is applied. In order to adapt the biological behavior to large-scale wireless mesh networks, we use a mesh topology for implementing the algorithm. Simulation results show that the total energy used and the decision time for routing of the proposed algorithm are improved under certain conditions.

• Journal of Communications and Networks
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• 제5권1호
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• pp.43-54
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• 2003

Due to insufficient available bandwidth resources and the continuously growing demand for cellular communication services, the channel assignment problem has become increasingly important. To trace the optimal assignment, several heuristic strategies have been proposed. So far, most of them focus on the small-scale systems containing no more than 25 cells and they use an anachronistic cost model, which does not satisfy the requirements ity. Solving the small-scale channel assignment problems could not be applied into existing large scale cellular networks' practice. This article proposes a decomposition approach to solve the fixed channel assignment problem (FCAP) for large-scale cellular networks through partitioning the whole cellular network into several smaller sub-networks and then designing a sequential branch-and-bound algorithm that is made to solve the FCAP for them sequentially. The key issue of partition is to minimize the dependences of the sub-networks so that the proposed heuristics for solving smaller problems will suffer fewer constraints in searching for better assignments. The proposed algorithms perform well based on experimental results and they were applied to the Taiwan Cellular Cooperation (TCC) in ChungLi city to find better assignments for its network.

• 대한임베디드공학회논문지
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• 제14권4호
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• pp.177-186
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• 2019

In wireless sensor networks, the transmission success ratio would be decreased when the scale of the WSNs increased. To defeat this problem, we propose a multipath routing based on opportunistic routing for improving end-to-end reliability in large-scale wireless sensor networks. The proposed scheme exploits the advantages of existing opportunistic routing and achieves high end-to-end success ratio by branching like a multipath routing through local decision without information of the whole network. As a result of the simulation result, the proposed scheme shows a similar or higher end-to-end transmission success ratio and less energy consumption rather than the existing scheme.

• Interdisciplinary Bio Central
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• 제3권2호
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• pp.8.1-8.6
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• 2011

Background: Thanks to the development of the mathematical/statistical reverse engineering and the high-throughput measuring biotechnology, lots of biologically meaningful genegene interaction networks have been revealed. Steady-state analysis of these systems provides an important clue to understand and to predict the systematic behaviours of the biological system. However, modeling such a complex and large-scale system is one of the challenging difficulties in systems biology. Results: We introduce a new stochastic modeling approach that can describe gene regulatory mechanisms by dividing two (DNA and protein) layers. Simple queuing system is employed to explain the DNA layer and the protein layer is modeled using G-networks which enable us to account for the post-translational protein interactions. Our method is applied to a transcription repression system and an active protein degradation system. The steady-state results suggest that the active protein degradation system is more sensitive but the transcription repression system might be more reliable than the transcription repression system. Conclusions: Our two layer stochastic model successfully describes the long-run behaviour of gene regulatory networks which consist of various mRNA/protein processes. The analytic solution of the G-networks enables us to extend our model to a large-scale system. A more reliable modeling approach could be achieved by cooperating with a real experimental study in synthetic biology.

• 센서학회지
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• 제26권1호
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• Journal of Communications and Networks
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• 제11권2호
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• pp.157-165
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• 2009

In this paper, we investigate a dynamic spectrum sharing problem for the centralized uplink cognitive radio networks using orthogonal frequency division multiple access. We formulate a large-scale joint rate and power allocation as an optimization problem under quality of service constraint for secondary users and interference constraint for primary users. We also suggest admission control to nd a feasible solution to the optimization problem. To implement the resource allocation on a large-scale, we introduce a notion of using the conservative factors $\alpha$ and $\beta$ depending on the outage and violation probabilities. Since estimating instantaneous channel gains is costly and requires high complexity, the proposed algorithm pursues a practical and implementation-friendly resource allocation. Simulation results demonstrate that the large-scale joint rate and power allocation incurs a slight loss in system throughput over the instantaneous one, but it achieves lower complexity with less sensitivity to variations in shadowing statistics.

• 한국컴퓨터정보학회논문지
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• 제10권4호
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• pp.239-248
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• 2005

대규모 무선 센서 네트워크는 네트워크의 신뢰성과 에너지 효율을 동시에 고려해야 한다. 네트워크의 신뢰성을 높이기 위해서는 유니 캐스트 기반 데이터 전송 방법보다 브로드캐스트 기반 데이터 전송 방법을 사용해야 한다. 최근 발표된 GRAdient Broadcast (GRAB)는 브로드캐스트 기반 데이터 전송으로 네트워크의 신뢰성을 높일 수 있다. 하지만 한 개의 sink를 사용하기 때문에 네트워크 전체 에너지를 고르게 사용하지 못한다. 결국 네트워크의 동작 시간이 단축되는 단점이 있다. 이에 본 논문에서는 대규모 무선센서 네트워크에 적합한 Selective Multi Sink Gradient Broadcast (SMSGB)를 제안한다. SMSGB 는 여러 개의 sink를 사용하여 네트워크를 구성하고 한 개의 sink만 데이터를 수집한다. 특정한 이벤트가 발생이 되면 다른 sink가 데이터를 수집하게 된다. 이러한 방법을 통해 전체 네트워크의 에너지를 고르게 소모 할 수 있다. 또한 GRAB와 동일한 브로드캐스트 기반 데이터 전송으로 대규모 무선 센서 네트워크에서 신뢰성을 보장할 수 있다. 기존의 GRAB와 SMSGB를 비교한 모의실험을 통해 GRAB와 비슷한 신뢰성을 유지하면서 GRAB보다 SMSGB의 네트워크 동작 시간이 약 18% 이상 연장됨을 보인다.

• 천문학회보
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• 제45권1호
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• pp.49.3-49.3
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• 2020

I will give an overview of the recent work in deriving cosmological constraints from deep learning methods applied to the large scale distribution of galaxies. I will specifically highlight the success of convolutional neural networks in linking the morphology of the large scale matter distribution to dark energy parameters and modified gravity scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권4호
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• pp.452-474
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• 2010

Formidable growth of Internet technologies has revealed challenging issues about its scale and performance evaluation. Modeling and simulation play a central role in the evaluation of the behavior and performance of the large-scale network systems. Large numbers of nodes affect simulation performance, simulation execution time and scalability in a weighty manner. Most of the existing simulators have numerous problems such as size, lack of system theoretic approach and complexity of modeled network. In this work, a scalable discrete-event modeling approach is described for studying networks' scalability and performance traits. Key fundamental attributes of Internet and its protocols are incorporated into a set of simulation models developed using the Discrete Event System Specification (DEVS) approach. Large-scale network models are simulated and evaluated to show the benefits of the developed network models and approaches.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.