• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.199-202
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• 2009

Adaptive memory management is a serious issue in data stream management. Data stream differ from the traditional stored relational model in several aspect such as the stream arrives online, high volume in size, skewed data distributions. Data skew is a common property of massive data streams. We propose the predicted allocation strategy, which uses predictive processing to cope with time varying data skew. This processing includes memory usage estimation and indexing with timestamp. Our experimental study shows that the predictive strategy reduces both required memory space and latency time for skewed data over varying time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1241-1246
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• 2005

This paper proposes an adaptive multislot allocation algorithm in order to achieve larger system capacity and higher throughput data transmissions. The proposed system is the combination of the slow adaptive modulation system, in which the base station dynamically assigns optimum modulation parameters measuring the SNR of each transmission terminal, and the multislot allocation scheme, in which the base station flexibly allocates an appropriate number of TDMA data slots according to the instantaneous load conditions. Computer simulations confirm that the proposed system can tremendously improve average message delay characteristics in comparison with the conventional fixed slot allocation method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.2
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• pp.11-18
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• 1995

Error detection in ARQ(Automatic Repeat Request) protocols is very important in wireless data communication systems. The throughput efficiency of ARQ protocols can be improved by dynamically adapting the protocol packet length so that it approaches the optimum value for throuhput efficiency. In this paper, a simple and novel adaptive packet length allocation method is proposed which transmits the packets with variable length by dyanmically estimating the channel codition. The simulation results show that the average of throughput is improved by 315.4% in the stop-and-wait protocol, 41.4% in the go-back-N protocol and 155.9% in the selective repeat protocol respectively. And the throughput performances of adaptive packet length allocation method approximately approach the theoritically optimal throughput performances.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.387-396
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• 2016

Multiuser communication has been an important research area of underwater acoustic communications and networking. This paper studies the use of adaptive orthogonal frequency-division multiple access (OFDMA) in a downlink scenario, where a central node sends data to multiple distributed nodes simultaneously. In practical implementations, the instantaneous channel state information (CSI) cannot be perfectly known by the central node in time-varying underwater acoustic (UWA) channels, due to the long propagation delays resulting from the low sound speed. In this paper, we explore the CSI feedback for resource allocation. An adaptive power-bit loading algorithm is presented, which assigns subcarriers to different users and allocates power and bits to each subcarrier, aiming to minimize the bit error rate (BER) under power and throughput constraints. Simulation results show considerable performance gains due to adaptive subcarrier allocation and further improvement through power and bit loading, as compared to the non-adaptive interleave subcarrier allocation scheme. In a lake experiment, channel feedback reduction is implemented through subcarrier clustering and uniform quantization. Although the performance gains are not as large as expected, experiment results confirm that adaptive subcarrier allocation schemes based on delayed channel feedback or long term statistics outperform the interleave subcarrier allocation scheme.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.625-632
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• 2000

This paper proposes an adaptive multislot allocation algorithm in order to achieve large system capacity and higher throughput data transmissions. The proposed system is the combination of the slow adaptive modulation system, in which the base station dynamically a signs optimum modulation parameters measuring the CNR(carrier to noise power ratio) of each transmission terminal, and the multislot allocation scheme, in which the base station flexibly allocates an appropriate number of TDMA data slots according to the instantaneous load conditions. Computer simulations confirm that the proposed system can tremendously improve average message delay characteristics in comparison with the conventional fixed slot allocation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1733-1751
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• 2015

The IEEE 802.15.4 standard not only provides a maximum of seven guaranteed time slots (GTSs) for allocation within a superframe to support time-critical traffic, but also achieves ultralow complexity, cost, and power in low-rate and short-distance wireless personal area networks (WPANs). Real-time wireless body area sensor networks (WBASNs), as a special purpose WPAN, can perfectly use the IEEE 802. 15. 4 standard for its wireless connection. In this paper, we propose an adaptive GTS allocation scheme for real-time WBASN data transmissions with different priorities in consideration of low latency, fairness, and bandwidth utilization. The proposed GTS allocation scheme combines a weight-based priority assignment algorithm with an innovative starvation avoidance scheme. Simulation results show that the proposed method significantly outperforms the existing GTS implementation for the traditional IEEE 802.15.4 in terms of average delay, contention free period bandwidth utilization, and fairness.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.38-55
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• 2013

Wireless network systems provide fast data transmission rates and various services to users of mobile devices such as smartphones and smart pads. Because many people use high-performance mobile devices, the use of real-time multimedia services is increasing rapidly. However, the preoccupation of resources by real-time traffic users is causing harm to other services-for example, frequent call interference, lowered service quality, and poor network performance. This paper suggests a resource allocation algorithm for effective traffic service support in a hybrid network. The main objective is to obtain an optimum value of data rates by comparing user requirements with the amount of resources that can be allocated. A new mechanism based on Adaptive-Quality of Service (QoS) and a monitoring system based on Queue-Aware are proposed. Adaptive-QoS supports effective resource control according to the type of traffic service, and the monitoring system based on Queue-Aware measures the amount of resources in order to calculate the maximum that can be allocated. We apply our algorithm to a test system and use Qualnet 4.5.1 to evaluate its performance.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.3
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• pp.33-46
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• 2007

This study deals with the adaptive multiuser OFDM (Orthogonal Frequency Division Multiplexing) system which adjusts the resource allocation according to the environmental changes in such as wireless and quality of service required by users. The resource allocation includes subcarrier assignment to users, modulation method and power used for subcarriers. We first develop a general optimization model which maximizes data throughput while satisfying data rates required by users and total power constraints. Based on the property that this problem has the 0 duality gap, we apply the subgradient dual optimization method which obtains the solution of the dual problem by iteration of simple calculations. Extensive experiments with realistic data have shown that the subgradient dual method is applicable to the real world system, and can be used as a dynamic resource allocation mechanism.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.2
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• pp.42-60
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• 1992

An adaptive fuzzy system can efficiently classify subimages into four categories according to image activity level for image data compression. The system estimates fuzzy rules by clustering input-output data generated from a given adaptive transform image coding process. The system encodes different images without modification and reduces side information when encoding multiple images. In the second part, a fuzzy system estimates optimal bit maps for the four subimage classes in noisy channels assuming a Gauss-Markov image model. The fuzzy systems respectively estimate the sampled subimage classification and the bit-allocation processes without a mathematical model of how outputs depend on inputs and without rules articulated by experts.