• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2340-2349
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• 2009

In this paper we proposed a hopping routing scheme to resolve the hot spot problem for periodic monitoring services in wireless sensor networks. Our hopping routing scheme constructs load balanced routing path, where an amount of energy consumption of all nodes in the sensor networks is predictable. Load balanced routing paths can be obtained from horizontal hopping transmission scheme which balances the load of the sensor nodes in the same area, and also from vertical hopping transmission scheme which balances the load of the sensor nodes in the other area. The direct transmission count numbers as load balancing parameter for vertical hopping transmission are derived using the energy consumption model of the sensor nodes. The experimental results show that the proposed hopping scheme resolves the hot spot problem effectively. The efficiency of hopping routing scheme is also shown by comparison with other routing scheme such as multi-hop, direct transmission and clustering.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.458-467
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• 2009

Long Tenn Evolution (LTE) is the next generation mobile phone technology which has being standardized by the Third Generation Partnership Project (3GPP). In the existing mobile communication networks, voice traffic is delivered through circuit switched networks. In LTE, however, all kinds of traffic are transferred through IP based packet switched networks which has best-effort characteristic. Therefore, providing QoS in LTE system is difficult. In order to provide QoS in LTE, RRM is very important. Especially, in part of RRM, call admission control (CAC) performs an important function to reduce network congestion and guarantee a certain level of QoS for on-going calls. In this paper, we propose a CAC algorithm in order to provide QoS for various kinds of services in LTE system. The performance of the proposed algorithm is evaluated with various simulation environments. The results show that the proposed algorithm provides QoS through rejections of requested calls. Especially, the proposed CAC algorithm can be satisfied with packet delay requirement defined in LTE specification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.889-896
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• 2007

Advances in wireless networking, micro-fabrication and integration, and embedded microprocessors have enabled a new generation of massive-scale sensor networks. Because each sensor node is limited in size and capacity, it is very important to design a new simple and energy efficient protocol. Among conventional sensor networks' routing protocols, the directed diffusion scheme is widely blown because of its simplicity. This scheme, however, has a defect in that sending interest and exploratory data messages while setting connection paths consumes much energy because of its flooding scheme. Therefore, this paper proposes a new sensor network routing protocol, called sequenced directed diffusion with a threshold control, which compromises the conventional directed diffusion scheme's defect and offers an energy efficient routing idea. With a computer simulation, its performance is evaluated and compared to the conventional directed diffusion scheme. Numerical results show that the proposed scheme offers energy efficiency while routing packets, and resolves ill-balanced energy consumption among sensor nodes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1256-1262
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• 2008

In mobile broadcasting networks, handover is an important issue to support seamless mobility. DVB-H(Digital Video Broadcasting for Handheld) standard was developed to enhance mobile features for DVB-T(Digital Video Broadcasting -Terrestrial) standard. This paper proposes new approaches for improving handover performance in the DVB-H networks. The proposed handover schemes are targeted to two different DVB-H receivers: One is for the receivers equipped with GPS devices. The other is for ones without GPS support. The first handover approach modifies the cell description table (CDT) proposed in the literature [1]. The second proposes a novel estimation technique of predefined handover region based on a new handover map table (HMT). This new handover approach estimates a predefined handover region with the measured RSSI(Received Signal Strength Indication) signal patterns. Using proposed handover algorithm, we can reduce time and power consumption. Through the computer simulations, we evaluate the performance of handover algorithm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.179-186
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• 2008

In proportion as the growth of the wireless sensor network applications, we need for more accuracy wireless channel information. In the case of indoor or outdoor wireless sensor networks, multipath propagation causes severe problems in terms of fading. Therefore, a path-loss model for multipath environment is required to optimize communication systems. This paper deals with log-normal path loss modeling of the indoor 2.4 GHz channel. We measured variation of the received signal strength between the sender and receiver of which separation was increased from 1 to 30m. The path-loss exponent and the standard deviation of wireless channel were determined by fitting of the measured data. By using the PRR(Packet Reception Rate) of this model. Wireless sensor channel is defined CR(Connect Region), DR(Disconnected Region). In order to verify the characteristics of wireless channel, we performed simulations and experiments. We demonstrated that connection ranges are 24m in indoor, and 14m in outdoor.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.97-103
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• 2020

Wireless sensor networks collect and analyze sensing data in a variety of environments without human intervention. The sensor network changes its lifetime depending on routing protocols initially installed. In addition, it is difficult to modify the routing path during operating the network because sensors must consume a lot of energy resource. It is important to measure the network performance through simulation before building the sensor network into the real field. This paper proposes a WSN model for a low-energy adaptive clustering hierarchy protocol using DEVS kernel models. The proposed model is implemented with the sub models (i.e. broadcast model and controlled model) of the kernel model. Experimental results indicate that the broadcast model based WSN model showed lower CPU resource usage and higher message delivery than the broadcast model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3412-3432
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• 2019

Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes' energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV's velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.55-62
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• 2019

Convolutional neural networks (CNNs) show high performance in the computer vision, but they require an enormous amount of operations, making them unsuitable for some resource- or energy-starving environments like the embedded environments. To overcome this problem, there have been much research on accelerators or pruning of CNNs. The previous pruning schemes have not considered the architecture of CNN accelerators, so the accelerators for the pruned CNNs have some inefficiency. This paper proposes a new pruning scheme, Conv-XP, which considers the architecture of CNN accelerators. In Conv-XP, the pruning is performed following the 'X' or '+' shape. The Conv-XP scheme induces a simple architecture of the CNN accelerators. The experimental results show that the Conv-XP scheme does not degrade the accuracy of CNNs, and that the accelerator area can be reduced by 12.8%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.1011-1017
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• 2019

This paper proposes reinforcement learning to solve the node-disjoint path problem which establishes multipath for reliable data transmission in wireless ad-hoc networks. The node-disjoint path problem is a problem of determining a plurality of paths so that the intermediate nodes do not overlap between the source and the destination. In this paper, we propose an optimization method considering transmission distance in a large-scale wireless ad-hoc network using Q-learning in reinforcement learning, one of machine learning. Especially, in order to solve the node-disjoint path problem in a large-scale wireless ad-hoc network, a large amount of computation is required, but the proposed reinforcement learning efficiently obtains appropriate results by learning the path. The performance of the proposed reinforcement learning is evaluated from the viewpoint of transmission distance to establish two node-disjoint paths. From the evaluation results, it showed better performance in the transmission distance compared with the conventional simulated annealing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5701-5722
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• 2018

The continuous increase in the cost of energy production and concerns for environmental sustainability are leading research communities, governments and industries to amass efforts to reduce energy consumption and global $CO_2$ footprint. Players in the information and communication industry are keen on reducing the operational expenditures (OpEx) and maintaining the profitability of cellular networks. Meanwhile, network virtualization has been proposed in this regard as the main enabler for 5G mobile cellular networks. In this paper, we propose a generic framework of slice resource provisioning and customized physical resource allocation for energy-efficiency and quality of service optimization. In resource slicing, we consider user demand and population resources provisioning scheme aiming to satisfy quality of service (QoS). In customized physical resource allocation, we formulate this problem with an integer non-linear programming model, which is solved by a heuristic algorithm based on minimum vertex coverage. The proposed algorithm is compared with the existing approaches, without consideration of slice resource constraints via system-level simulations. From the perspective of infrastructure providers, traffic is scheduled over a limited number of active small-cell base stations (sc-BSs) that significantly reduce the system energy consumption and improve the system's spectral efficiency. From the perspective of virtual network operators and mobile users, the proposed approach can guarantee QoS for mobile users and improve user satisfaction.