• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1208-1222
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• 2014

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.44-47
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• 2011

In this paper, we propose context-aware based on Low Power Sensing Algorithm. The proposed sensing algorithm reduces power consumptions using low-power sensing algorithms and low-power sensing protocols. Experimental results show that the average power consumption of the proposed method is up to half consumption that of the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.141-150
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• 2005

Wireless Sensor Networks have been rapidly developed due to the advances of sensor technology and are expected to be applied to various applications in many fields. In Wireless Sensor Networks, schemes for managing the network energy-efficiently are most important. For this purpose, there have been a variety of researches to suggest routing protocols. However, existing researches have ideal assumption that all sensor nodes have sensing data to transmit. In this paper, we designed and implemented a sensing-aware cluster selection algorithm based on LEACH-C for the sensor network in which part of sensors have sensing data. We also simulated proposed algorithm on several network situation and analyzed which situation is suitable for the algorithm. By the simulation result, selecting cluster head among the sensing nodes is most energy-efficient and the result shows application of sensing-awareness in cluster head selection when not all sensors have sensing data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1090-1105
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• 2012

A multi-modal sensing M2M healthcare monitoring system for the continuous monitoring of patients under their natural physiological states or elderly persons with chronic diseases is summarized. The system is designed for homecare or the monitoring of the elderly who live in country side or small rest home without enough support from caregivers or doctors, instead of patient monitoring in big hospital environment. Further insights into the natural cause and progression of diseases are afforded by context-aware sensing, which includes the use of accelerometers to monitor patient activities, or by location-aware indoor tracking based on ultrasonic and RF sensing. Moreover, indoor location tracking provides information about the location of patients in their physical environment and helps the caregiver in the provision of appropriate support.

• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1088-1098
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• 2005

Context-Aware is a one of the important researches in ubiquitous computing for providing optimal service to users by acquiring user's intentions and environmental information. Diverse researches are focused on the users and its environment facts for Context-Aware base and introduce a sensing based middleware which engages sever/sensor that operates identifier information to provide services. Context-Aware service which is limited by users and environment facts has the problem of overlapping sensing, unnecessary searching and anonymity of users. Also Server-Centric Context-Aware system requires very high cost to manage and operate the services. On this paper, We introduce Autogenous Context service model to simplify the Context-Aware process and design the middleware which performs decentralize management for Context-Aware information of user's portable devices to minimize problems which is occurred during the management and operation of existing Context-Aware system.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.581-588
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• 2014

To facilitate the implementation of a wide variety of context-aware applications based on mobile devices, general-purpose context-aware framework that applications can use by calling is needed. The context-aware framework is a middleware that performs the sensing, reasoning, and retrieving based on the knowledge base. The knowledge base must systematically represent the information required on the behavior of the context-aware framework, such as context information and reasoning information. It must also provide functions for storage and retrieval. To date, previous research on the representation of the context information have been carried out, but studies on the unified representation of the knowledge base has seen little progress. This study defines the knowledge base as the unified context information, and proposes the UniOWL, which can do a good job of representing it. UniOWL is based on OWL and represents the information that is necessary for the operation of the context-aware framework. Therefore, UniOWL greatly facilitates the implementation of the knowledge base on a context-aware framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.248-268
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• 2018

The performance of smartphone applications are usually constrained in user interactions due to resource limitation and it promises great opportunities to improve the performance by exploring the smartphone built-in and embedded sensing techniques. However, heterogeneity in techniques, semantic gap between sensor data and usable context, and complexity of contextual situations keep the techniques from seamless integration. Relevant studies mainly focus on feasibility demonstration of emerging sensing techniques, which rarely address both general architectures and comprehensive technical solutions. Based on a proposed functional model, this investigation provides a general architecture to deal with the dynamic context for context-aware automation and decision support. In order to take advantage of the built-in sensors to improve the performance of mobile applications, an ontology-based method is employed for context modelling, linguistic variables are used for heterogeneous context presentation, and semantic distance-based rule matching is employed to customise functions to the contextual situations. A case study on mobile application authentication is conducted with smartphone built-in hardware modules. The results demonstrate the feasibility of the proposed solutions and their effectiveness in improving operational efficiency.

• Journal of KIISE
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• v.43 no.7
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• pp.763-772
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• 2016

With the spread of smartphones containing multiple on-board sensors, the market for context aware applications have grown. However, due to the limited power capacity of a smartphone, users feel discontented QoS. Additionally, context aware applications require the utilization of many forms of context and sensing information. If context transition has occurred, types of needed sensors must be changed and each sensor modules need to turn on/off. In addition, excessive sensing has been found when the context decision is ambiguous. In this paper, we focus on power consumption associated with the context transition that occurs during indoor/outdoor detection, modeling the activities of the sensor associated with these contexts. And we suggest a freezing algorithm that reduces power consumption in context transition. We experiment with a commercial application that service is indoor/outdoor location tracking, measure power consumption in context transition with and without the utilization of the proposed method. We find that proposed method reduces power consumption about 20% during context transition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.552-555
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• 2010

In this paper, we propose a context-aware system using wireless multi sensor module to monitor the state for industrial factory environment. Wireless multi sensor module combines sensing values which are collected from each acceleration, pressure, temperature and gas sensors. Moreover, it delivers this data to server after being encoded by RS code. Thereafter, RS decoder decodes the values that are received from wireless multi sensor module and fixes errors which occur in wireless communication. Based on decoded data, context-aware algorithm sets critical range and compares it to the sensing values, if the sensing values are out of the range, an event occurs by the algorithm. At the same time, if there is another sensing value which is out of the range for standby time T seconds, the algorithm orders 3 steps-alarm to occur depending on each situation. Through this system, it becomes eventually possible to monitor machines' condition effectively. From the simulation, we confirm that this system is efficient to status monitoring of industrial automation equipment.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.295-309
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• 2016

Spectrum sensing is an essential function that enables cognitive radio technology to explore spectral holes and resourcefully access them without any harmful interference to the licenses user. Spectrum sensing done by a single node is highly affected by fading and shadowing. Thus, to overcome this, cooperative spectrum sensing was introduced. Currently, the advancements in multiple antennas have given a new dimension to cognitive radio research. In this paper, we propose a multiple energy detector for cooperative spectrum sensing schemes based on the evidence theory. Also, we propose a reporting mechanism for multiple energy detectors. With our proposed system, we show that a multiple energy detector using a cooperative spectrum sensing scheme based on evidence theory increases the reliability of the system, which ultimately increases the spectrum sensing and reduces the reporting time. Also in simulation results, we show the probability of error for the proposed system. Our simulation results show that our proposed system outperforms the conventional energy detector system.