• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.358-370
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• 2007

Software simulations have been widely used for the design and application development of a wireless sensor network that is an infrastructure of ubiquitous computing. In this study, we develop a sensor network simulator that can verify the behavior of sensor network applications, estimate execution time and power consumption, and simulate a large-scale sensor network. To implement the simulator, we use an instruction-level parallel discrete-event simulation method. Instruction-level simulation uses executable images loaded into a real sensor board as workload, such that it results in the high degree of details. Parallel simulation makes simulation of a large-scale sensor network possible by distributing workload into multiple computers. The simulator can predict the amount of power consumption based on operating time of modules in a sensor node and counting the number of executed instructions by kind. Also it can simulate ubiquitous applications with various scenarios and debug programs. Instruction traces used as workload for simulations are executable images produced by the cross-compiler for ATmega128L microcontroller.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.129-137
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• 2010

In this paper, we propose a packet prioritization scheme using preamble signal and backoff time which is designed to provide a differentiated channel occupation with a packet priority in wireless sensor networks. This scheme aims at enabling QoS such as fast delivery of high priority packets by reducing their backoff time as well as thus securing higher channel occupation. We expect that it could also improve the channel utilization of the entire network by avoiding unnecessary channel contention. For the purpose, we add new features of multiple queue and preamble modification to the TinyOS based B-MAC. This scheme achieves 82-88% reduction in delivery time of high priority packets, thus it enables realtime support for urgent applications.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.183-192
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• 2012

Although underground water resource has relatively less pollution rate compared with surface water, its recovery faces many difficulties due to poor management. Our country monitors underground water to manage it effectively through auxiliary observation network for underground water. In this paper, we suggest water-well auto measure system based on Geosensor for business efficiency increase of water-well management and realtime monitering. In this system is consist of user GUI(Graphic User Interface) composed with water-well information and movement sub-observation network prototype system composed with GPS(Global Positioning System) and wireless sensor node such as water temperature, water level, electrical conductivity. In this system is using the light of the sun for self-power, variety water-well information collected wireless sensor node was a wireless transmitting/receiving a using CDMA(Code Division Multiple Access) module. Also, for promote with user ease, user GUI express that water-well collected in GIS(Geographic Information System) map. For performance evaluation of the proposed system, we perform experiment using sensing information through designed sub-observation network. And we was proved superiority of the proposed system through qualitative evaluation with other paper.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.105-112
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• 2015

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.91-98
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• 2010

This study proposes a monitoring system that effectively watches surroundings by cooperating the various sensor information including image information on a sensor network system. The monitoring system proposed in this paper is developed to watch certain intruders to the internal spaces through the interested region for exceptional time by installing cameras, PIR(Pyroelectric Infrared Ray) sensor and body detectors in such interested regions. Moreover the monitering system is implemented based on the SenWeaver plateform which is a integrated development tools for building wireless sensor network system. In the results of the test that was applied to a practically experimental environment by implementing some interfaces for the proposed system, it was considered that it is possible to watch surroundings effectively using the image information obtained from cameras and multiple sensor information acquisited from sensor nodes.

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.139-148
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• 2008

Many types of sensor data exhibit strong correlation in both space and time. Suppression, both temporal and spatial, provides opportunities for reducing the energy cost of sensor data collection. Unfortunately, existing clustering algorithms are difficult to utilize the spatial or temporal opportunities, because they just organize clusters based on the distribution of sensor nodes or the network topology but not correlation of sensor data. In this paper, we propose a novel clustering algorithm with suppression techniques. To guarantee independent communication among clusters, we allocate multiple channels based on sensor data. Also, we propose a spatio-temporal suppression technique to reduce the network traffic. In order to show the superiority of our clustering algorithm, we compare it with the existing suppression algorithms in terms of the lifetime of the sensor network and the site of data which have been collected in the base-station. As a result, our experimental results show that the size of data was reduced by $4{\sim}40%$, and whole network lifetime was prolonged by $20{\sim}30%$.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.157-164
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• 2008

In this paper we suggest a scheduling algorithm that transmits periodic traffics efficiently in tree-structured wireless sensor networks (WSNs). The related research[l] showed the problems such as increasing the energy consumption and decreasing the data throughput as the depth of tree increases. To solve these problems. we use idle time slots and avoid the redundancy at data transmission. Also we suggest the algorithm that transmits the control packet when it is similar to a previously measured data. And if emergency data is occurred, our proposed algorithm transits that data in EDP(Emergency Data Period) for reducing the wait time. The proposed algorithm shows more data throughput and less energy consumption than that of the related research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1756-1776
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• 2012

Wireless sensor networks (WSNs) are likely to be more prevalent as their cost-effectiveness improves. The spectrum of applications for WSNs spans multiple domains. In environmental sciences, in particular, they are on the way to become an essential technology for monitoring the natural environment and the dynamic behavior of transient physical phenomena over space. Existing sensor network query processors (SNQPs) have also demonstrated that in-network processing is an effective and efficient means of interaction with WSNs for performing queries over live data. Inspired by these findings, this paper investigates the question as to whether spatio-temporal and historical analysis can be carried over WSNs using distributed query-processing techniques. The emphasis of this work is on the spatial, temporal and historical aspects of sensed data, which are not adequately addressed in existing SNQPs. This paper surveys the novel approaches of storing the data and execution of spatio-temporal and historical queries. We introduce the challenges and opportunities of research in the field of in-network storage and in-network spatio-temporal query processing as well as illustrate the current status of research in this field. We also present new areas where the spatio-temporal and historical query processing can be of significant importance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.1-9
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• 2016

Railroad bridges account for 25% of the entire high-speed rail network. Railway bridges are subject to gradual structural degradation or fatigue accumulation due to consistent and repeating excitation by fast moving trains. Wireless sensing technology has opened up a new avenue for bridge health monitoring owing to its low-cost, high fidelity, and multiple sensing capability. On the other hand, measuring the transient response during train passage is quite challenging that the current wireless sensor system cannot be applied due to the intrinsic time delay of the sensor network. Therefore, this paper presents a framework for monitoring such transient responses with wireless sensing systems using 1) real-time excessive vibration monitoring through ultra-low-power MEMS accelerometers, and 2) post-event time synchronization scheme. The ultra-low power accelerometer continuously monitors the vibration and trigger network when excessive vibrations are detected. The entire network of wireless smart sensors starts sensing through triggering and the post-event time synchronization is conducted to compensate for the time error on the measured responses. The results of this study highlight the potential of detecting the impact load and triggering the entire network, as well as the effectiveness of the post-event time synchronized scheme for compensating for the time error. A numerical and experimental study was carried out to validate the proposed sensing hardware and time synchronization method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.512-519
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• 2016

This paper presents spectrum utilization strategies in cognitive radio (CR) networks powered by multi-antenna based wireless energy transfer. Secondary access point (AP) with multiple antennas should transfer the energy to the secondary sensor nodes with energy beamforming and simultaneously induces no interference to PUs. In addition, sensor nodes can transmit information to the secondary AP using the harvested energy, only when the spectrum is not utilized by PUs. We analyze the achievable rate of the CR sensor networks and propose an interference nulling energy beamforming method to maximize the achievable rate. Finally, we also propose a frame scheduling algorithm in which the durations of wireless energy transfer/information transfer frames (phases) are optimized.