• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1113-1128
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• 2020

Ad hoc networks play an important role in mobile communications, and the performance of nodes has a significant impact on the choice of communication links. To ensure efficient and secure data forwarding and delivery, an intelligent routing protocol (IAODV) based on learning method is constructed. Five attributes of node energy, rate, credit value, computing power and transmission distance are taken as the basis of segmentation. By learning the selected samples and calculating the information gain of each attribute, the decision tree of routing node is constructed, and the rules of routing node selection are determined. IAODV algorithm realizes the adaptive evaluation and classification of network nodes, so as to determine the optimal transmission path from the source node to the destination node. The simulation results verify the feasibility, effectiveness and security of IAODV.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.6
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• pp.339-345
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• 2013

This paper addresses the system lifetime maximization algorithm in multi-hop sensor network system. A multi-hop sensor network consists of many battery-driven sensor nodes that collaborate with each other to gather, process, and communicate information using wireless communications. As sensor-driven applications become increasingly integrated into our lives, we propose a energy-aware scheme where each sensor node transmits informative data with adaptive data rate to minimize system energy consumption. We show the optimal data rate to maximize the system lifetime in terms of remaining system energy. Furthermore, the proposed algorithm experimentally shows longer system lifetime in comparison with greedy algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.1
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• pp.28-36
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• 2007

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, many researchers have studied on the energy management in the WSNs(Wireless Sensor Networks), especially taking into account communications efficiency. For effective data transmission and sensor fault detection in sensor network environment, a new remote monitoring system based on PCA(Principle Component Analysis) and AANN(Auto Associative Neural Network) is proposed. PCA and AANN have emerged as a useful tool for data compression and identification of abnormal data. Proposed system can be effectively applied to sensor network working in LEA2C(Low Energy Adaptive Connectionist Clustering) routing algorithms. To verify its applicability, some simulation studies on the data obtained from real WSNs are executed.

• 전자공학회논문지 IE
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• v.43 no.3
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• pp.41-48
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• 2006

In this paper, we propose a new active queue management (AQM) scheme by utilizing the predictability of the Internet traffic. The proposed scheme predicts future traffic input rate by using the auto-regressive (AR) time series model and determines the future congestion level by comparing the predicted input rate with the service rate. If the congestion is expected, the packet drop probability is dynamically adjusted to avoid the anticipated congestion level. Unlike the previous AQM schemes which use the queue length variation as the congestion measure, the proposed scheme uses the variation of the traffic input rate as the congestion measure. By predicting the network congestion level, the proposed scheme can adapt more rapidly to the changing network condition and stabilize the average queue length and its variation even if the traffic input level varies widely. Through ns-2 simulation study in varying network environments, we compare the performance among RED, Adaptive RED (ARED), REM, Predicted AQM (PAQM) and the proposed scheme in terms of average queue length and packet drop rate, and show that the proposed scheme is more adaptive to the varying network conditions and has shorter response time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7B
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• pp.628-640
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• 2004

The demand for next generation networks can be condensed into always-best-connected, ubiquitous, mobile, all-lP, and converged networks. IPv6 has been introduced for all-IP ubiquitous communications, and vehicles are coming to represent an important communication platform. In this paper. we propose various resource management schemes for in-vehicle mobile networks, which are adaptive to different hardware configurations. We focus on power and wireless bandwidth since they are critical resources for mobile communications. Based on the mobility characteristics of in-vehicle networks, we propose vehicle-aware power saving schemes. The main idea behind these power saving schemes is to adjust mobile router (MR) advertisement interval and binding lifetime. In addition, according to different wireless environments, we propose adaptive bandwidth management schemes using multihoming: best-connected MR selection based on location, and high-data-rate MR selection based on priority By mathematical analysis, it is shown that our schemes save power prominently for both the dormant nodes and active nodes. In addition, simulation results show that proposed multiple mobile router architecture outperforms previous simple redundant router architecture in preserving session and providing sufficient bandwidth.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.4
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• pp.395-403
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• 2005

It is very important to forecast water supply for reasonal operation and management of water utilities. In this paper, water supply forecasting models using artificial intelligence are developed. Artificial intelligence models shows better results by using Temperature(t), water supply discharge (t-1) and water supply discharge (t-2), which are expressed by neural network(LMNNWS; Levenberg-Marquardt Neural Network for Water Supply, MDNNWS; MoDular Neural Network for Water Supply) and neuro fuzzy(ANASWS; Adaptive Neuro-Fuzzy Inference Systems for Water Supply). ANFISWS model which is applied for water supply forecasting shows stable application to the variable water supply data. As results, MDNNWS model shows the highest overall accuracy among proposed water supply forecasting models and the lowest estimation error with the order of ANFISWS, LMNNWS model.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1043-1048
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• 2005

As sensor network is drawing more attention than ever before due to the development of sensors and the technology of communications, various routing-algorithms, to realize a sensor node with low-power and a miniature size, is being introduced in the field. This paper is to discuss a way to find an optimal path by changing a routing- algorithm adequately according to environmental changes. This is also to suggest an appropriate sensor network model in the ubiquitous aera. The result from the experiment that we conducted showed us that as we suggested, an algorithm, changing and adapting itself to each different environment, operated more stably and transmitted data more effectively than the current fixed one. And it was also confirmed that this type of algorithm can provide low-power management, which is very important in sensor network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.462-483
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• 2016

The research on optimization of cellular network's energy efficiency (EE) towards environmental and economic sustainability has attracted increasing attention recently. In this survey, we discuss the opportunities, trends and challenges of this challenging topic. Two major contributions are presented namely 1) survey of proposed energy efficiency metrics; 2) survey of proposed energy efficient solutions. We provide a broad overview of the state of-the-art energy efficient methods covering base station (BS) hardware design, network planning and deployment, and network management and operation stages. In order to further understand how EE is assessed and improved through the heterogeneous network (HetNet), BS's energy-awareness and several typical HetNet deployment scenarios such as macrocell-microcell and macrocell-picocell are presented. The analysis of different HetNet deployment scenarios gives insights towards a successful deployment of energy efficient cellular networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.581-593
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• 2002

In this paper, we proposed an Adaptive RIO scheme to solve the problem of RIO scheme that occurs when admission control is performed for QoS guarantee of Assured Service in Differentiated Services. To prevent an early random drop of the admitted In-profile packet, proposed Adaptive RIO scheme updates parameters of RIO scheme every time interval according to the estimated numbers of maximum packet arrivals of In-profile traffic and total traffic during the next time interval. The numbers of maximum packet arrivals during the next time interval are estimated based on the buffer size determined by the network topology and the ratio of bandwidth allocated to each subclass. We found from simulation results that, compared with RIO scheme, proposed Adaptive RIO scheme can improve performance of the throughput for In-profile traffic when admission control is performed or congestion occurs.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.217-219
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• 2006

4G mobile networks are expected to support various multimedia services over IP networks and also satisfy high spectral efficiency requirement. In cellular systems including 4G networks, hotspot cells can occur when available wireless resources at some location are not enough to sustain the needs of users. The hotspot cell can potentially lead to blocked and dropped calls, which can deteriorate the service quality for users. In a 4G mobile network, a band of users enjoying multimedia services can move around, which may generate heavy flows of traffic load. This situation can generate the hotspot cell which has a short life span of only a few minutes. In this paper, we propose a handover-based scheme which can effectively manage hotspot cells in 4G mobile networks. With the scheme, the current serving cell can recognize the load status of the target cell in advance before handover execution. Adaptive handover time control according to the amount of traffic load of cells can effectively and flexibly manage the hotspot cell in the network. And, through our hotspot cell management scheme, acceptable service quality can be supported as users continuously maintain connections with the network. In the simulation results, we find that our scheme generates smaller number of hotspot cells and supports higher service quality than the compared schemes.