• ETRI Journal
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• v.40 no.2
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• pp.227-236
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• 2018

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.37-44
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• 2017

Wireless sensor networks are composed of many wireless sensor nodes that are sensing the environments. These networks have many constraints that are resource constraints, wireless communication, self-construction, etc. But they have many applications that are monitoring environment, tracking the object, etc. In this paper, a mechanism of finding QoS Satisfied multi-path is proposed in wireless sensor networks. In order to satisfy the QoS requirement, the proposed mechanism extends the AODV protocol to find multiple paths from a source node to a destination node by using the additional AODV message types that are proposed. This mechanism will be used to support many QoS applications such as minimum delay time, the better reliability and the better throughput by using the QoS satisfied multi-path. Overheads of the proposed mechanism are evaluated using simulation, and it is showed that QoS satisfied multiple paths are found with a little more overhead than the AODV mechanism.

• Korean Management Science Review
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• v.11 no.2
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• pp.133-146
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• 1994

This study compares the performance of neural networks and ordinary least squares regression with quality-control processes. We examine the applicability of neural networks because they do not require any assumptions regarding either the functional from of the underlying process or the distribution of errors. The coefficient of determination($R^2$), mean absolute deviation(MAD), and the mean squared error(MSE) metrics indicate that neural networks are a viable and can be a superior technique. We also demonstrate that an assessment of the magnitude of the neural notwork input layer cumulative weights can be used to determine the relative importance of predictor variables.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.857-869
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• 2016

This paper proposes an X-MAC/BEB protocol that runs a binary exponential backoff (BEB) algorithm on top of an X-MAC protocol to save more energy by reducing collision, especially in densely populated wireless sensor networks (WSNs). X-MAC, a lightweight asynchronous duty cycle medium access control (MAC) protocol, was introduced for spending less energy than its predecessor, B-MAC. One of X-MAC 's conspicuous technique is a mechanism to allow senders to promptly send their data when their receivers wake up. X-MAC, however, has no mechanism to deal with sudden traffic fluctuations that often occur whenever closely located nodes simultaneously diffuse their sense data. To precisely evaluate the impact of the BEB algorithm on X-MAC, this paper builds an analytical model of X-MAC/BEB that integrates the BEB model with the X-MAC model. The analytical and simulation results confirmed that X-MAC/BEB outperformed X-MAC in terms of throughput, delay, and energy consumption, especially in congested WSNs.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.366-370
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• 1998

One major limitation of the efficiency of parallel computer designs has been the prohibitively high cost of parallel communication between processors and memories. Linear order concentrators can be used to build theoretically optimal interconnection schemes. Current designs call for building superconcentrators from concentrators, then using these to recursively partition the connection streams O(log2N) times to achieve point-to-point routing. Since the superconcentrators each have O(N) hardware complexity but O(log2N) depth, the resulting networks are optimal in hardware, but they are of O(log2N) depth. This pepth is not better than the O(log2N) depth Bitonic sorting networks, which can be implemented on the O(N) shuffle-exchange network with message passing. This paper introduces a new method of constructing networks using linear order concentrators and expanders, which can be used to build interconnection networks with O(log2N) depth as well as O(Nlog2N) hardware cost. (All logarithms are in base 2 throughout paper)

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.920-924
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• 2005

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the environment. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.156-162
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• 2008

Cooperative relays can provide spatial diversity and improve performance of wireless communications. In this paper, we study subcarrier power allocation at the relays for orthogonal frequency division multiplexing (OFDM)-based wireless systems. For cooperative relay with amplify-and-forward (AF) and decode-and-forward (DF) algorithms, we investigate the impact of power allocation to the mutual information between the source and destination. From our simulation results on word~error-rate (WER) performance, we find that the DF algorithm with power allocation provides better performance than that of AF algorithm in a single path relay network because the former is able to eliminate channel noise at each relay. For the multiple path relay network, however, the network structure is already resistant to noise and channel distortion, and AF approach is a more attractive choice due to its lower complexity.

• ETRI Journal
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• v.39 no.3
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• pp.345-352
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• 2017

Traffic management is a highly beneficial mechanism for satisfying quality-of-service requirements and overcoming the resource scarcity problems in networks. This paper introduces an optimal connection admission control mechanism to decrease the packet loss ratio and end-to-end delay in cognitive radio sensor networks (CRSNs). This mechanism admits data flows based on the value of information sent by the sensor nodes, the network state, and the estimated required resources of the data flows. The number of required channels of each data flow is estimated using a proposed formula that is inspired by a graph coloring approach. The proposed admission control mechanism is formulated as a semi-Markov decision process and a linear programming problem is derived to obtain the optimal admission control policy for obtaining the maximum reward. Simulation results demonstrate that the proposed mechanism outperforms a recently proposed admission control mechanism in CRSNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4774-4796
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• 2018

Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.

• Journal of Korea Multimedia Society
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• v.9 no.6
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• pp.735-741
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• 2006

In the near future, the wireless home networks will connect several devices at home. Due to the broadcast nature of a wireless network, anyone can hear and capture communication. Thus, we need to protect our network from attacks outside the house. In this paper, we propose and implement a security system that provides different levels of the security services to heterogenous home devices. To reduce the communication cost and workload of the server, home devices send the encrypted messages directly instead of sending through the sever. We implement our security system on laptops using JAVA and our security system achieves the better performance with the large number of devices and messages in a network. In order to prove that our security system is secure against various attacks, we analyze the security of our security system using attack trees.