• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.137-141
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• 2015

Mobile cloud computing uses cloud service to solve the resource constraint problem of mobile devices. Offloading means that a task executed on the mobile device commits to cloud and many studies related to the energy consumption have been researched. In this paper, we designed a response time model considering sensing data synchronization to estimate the efficiency of the offloading scheme in terms of the response time. The proposed model considers synchronization of required sensing data to improve the accuracy of response time estimation when cloud processes the task requested from a mobile device. We found that the response time is effected by new sensing data generation rate and synchronization period through simulation results.

• Smart Structures and Systems
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• v.18 no.5
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.245-248
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• 2004

In this paper, we propose a framework for synchronization of spatial data between mobile devices and a server by using SyncML(Synchronization Markup Language) that is standard specification for synchronization protocol. We used GML (Geographic Markup Language) to support interoperability of spatial data between various data sources. We also used metadata and catalog service to access and integrate distributed spatial data, considering relationships of spatial data and non-spatial data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.522-525
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• 2007

Frame Synchronization is applied to not only digital data transmission for data synchronization between transmitter and receiver but also data communication with satellite. When satellite image data with high resolution and mass storage is transmitted, hardware frame synchronizer for real-time processing or software frame synchronizer for post-processing is used. In case of hardware, processing with high speed is available but data loss may happen for Search of Frame Synchronization. In case of software, data loss does not happen but speed is relatively slow. In this paper, Pending Buffer concept was proposed to cope with data loss according to processing status of Frame Synchronization. Algorithm to process Frame synchronization with high speed using bit threshold search algorithm with pattern search technique and SIMD is also proposed.

• Smart Structures and Systems
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• v.18 no.3
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• pp.541-568
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• 2016

The goal of this study is to investigate the effect of non-synchronous sensing when using wireless sensors on structural identification and to attempt correcting such errors in order to obtain a better identification result. The sources causing non-synchronous sensing are discussed first and the magnitudes of such synchronization errors are estimated based on time stamps of data samples collected from Imote2 sensors; next the impact of synchronization errors on power spectral densities (PSDs) and correlation functions of output responses are derived analytically; finally a new method is proposed to correct such errors. In this correction method, the corrected PSDs of output responses are estimated using non-synchronous samples based on a modified FFT. The effect of synchronization errors in the measured output responses on structural identification and the application of this correction method are demonstrated using simulation examples. The simulation results show that even small synchronization errors in the output responses can distort the identified modal and stiffness parameters remarkably while the parameters identified using the proposed correction method can achieve high accuracy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.367-370
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• 2006

A GPS-based time synchronization technique employing a refined HW circuitry and SW algorithm is considered as fine time-management system for Low Earth Orbit (LEO) remote sensing satellites. By synchronizing the On-Board Time (OBT) within satellites to the GPS 1PPS, a very expensive, highly accurate on-board clock is not required to determine the precise on-board time management. Also, the satellite command generation in ground stations and postprocessing of earth observation data which a particular image is acquired. This paper analyses on-orbit verification of the existing satellite time sync architecture and presents a new time sync architecture, operation and relation between the OBT and the GPS time.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.228-231
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• 2008

For a satellite data communication, the technology of frame synchronization is widely used between a sender and a receiver. Last year, we suggested zero-loss frame synchronization [1] using pattern search and using bits threshold search algorithm that is based on SIMD technology [2,3]. This algorithm could solve both of hardware and software drawbacks, which are frame loss and low processing performance. However, this algorithm didn't optimize the processing of output data, synchronized data, which caused overhead to the memory allocation and the memory copy. Consequently, the performance of the frame synchronizer application was degraded. In this paper, we enhance previous work using a circular buffer in order to optimize the output data processing. The performance comparison with the previous algorithm shows that the enhanced proposed approach dramatically outperforms in the output data processing speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.613-631
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• 2013

Cognitive radio (CR) is proposed as a key solution to improve spectral efficiency and overcome the spectrum scarcity. Spectrum sensing is an important task in each CR system with the aim of identifying the spectrum holes and using them for secondary user's (SU) communications. Several conventional methods for spectrum sensing have been proposed such as energy detection, matched filter detection, etc. However, the main limitation of these classical methods is that the CR network is not able to communicate with its own base station during the spectrum sensing period and thus a fraction of the available primary frame cannot be exploited for data transmission. The other limitation in conventional methods is that the SU data frames should be synchronized with the primary network data frames. To overcome the above limitations, here, we propose a spectrum sensing technique based on blind source separation (BSS) that does not need time synchronization between the primary network and the CR. Moreover, by using the proposed technique, the SU can maintain its transmission with the base station even during spectrum sensing and thus higher rates are achieved by the CR network. Simulation results indicate that the proposed method outperforms the accuracy of conventional BSS-based spectrum sensing techniques.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.813-818
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• 2020

Recently, with the rapid increase in technology and users of smart devices, the smart watch market has grown, and its utility and usability are continuously expanding. The strengths of smartwatches are wearable portability, application immediacy, data diversity and real-time capability. Despite these strengths, smartwatches have limitations such as battery limitations, display and user interface size limitations, and memory limitations. In addition, there is a need to supplement developers and standard devices, operating system standard models, and killer application modules. In particular, monitoring and application of user's biometric information is becoming a major service for smart watches. The biometric information of such a smart watch generates a large amount of data in real time. In order to advance the biometric information service, stable peer-to-peer transmission of sensing data to a remote smartphone or local server storage must be performed. We propose a synchronization method to ensure wireless remote peer-to-peer transmission stability in a smart watch system. We design a wireless peer-to-peer transmission process based on this synchronization method, analyze asynchronous transmission process and proposed synchronous transmission process, and propose a transmission efficiency method according to an increase in transmission amount.

• Journal of the Korea Convergence Society
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• v.8 no.6
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• pp.163-170
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• 2017

In this paper want to recognize competition and cooperation as a non-contact sensing method among the social emotion that are caused by interaction. Experiments were conducted in a pattern matching task divided into competition and cooperation situations. Data collection was performed by extracting the micro-movement data of 15Hz component from the upper body image. We compared and analyzed the amount and the variation and synchronization. As a result, Amount and variation are bigger in competition than cooperation. Synchronization was higher in cooperation than competition. This can be seen as the difference between two people trying to win when they are in competition and trying to breathe each other in cooperation. This study is significant in confirming the possibility of competition and cooperation through non contact sensing method based on physiological response.