• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.626-633
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• 2006

The wireless sensor networks are sensing, computing and communication infrastructures that allow us to monitor, instrument, observe, and respond to phenomena in the harsh environment. Sensor operating systems that run on tiny sensor nodes are the key to the performance of the distributed computing environment for the wireless sensor networks. Therefore, sensor operating systems should be able to operate efficiently in terms of energy consumption and resource management. In this paper, we present an efficient memory allocation scheme to improve the time and space efficiency of memory management for the sensor operating systems. Our experimental results show that the proposed scheme performs efficiently in both time and space compared with existing memory allocation mechanisms.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.11
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• pp.572-580
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• 2007

Wireless sensor networks are sensing, computing and communication infrastructures that allow us to monitor, instrument, observe, and respond to phenomena in the harsh environment. Generally, the wireless sensor networks are composed of many deployed sensor nodes that were designed to be very cost-efficient in terms of production cost. For example, UC Berkeley's MICA motes have only 8-bit CPU, 4KB RAM, and 128KB FLASH memory space. Therefore, sensor operating systems that run on the sensor nodes should be able to operate efficiently in terms of the resource management. In this paper, we present a dynamic threads stack management scheme for space-constrained and multi-threaded sensor operating systems. In this scheme, the necessary stack space of each function is measured on compile-time. Then, the information is used to dynamically allocate and release each function's stack space on run-time. It was implemented in Nano-Qplus sensor operating system. Our experimental results show that the proposed scheme outperforms the existing fixed-size stack allocation mechanism.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.437-441
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• 2010

A new application area in which wireless sensor networks are applied requires the performance of more elaborated and complicated task and the completion of those tasks within a time limit. Until now, it is, however, insufficient to do research on the mechanism of handling interrupt based on real-time sensor operating systems which carefully consider the limitation of resources of sensor nodes and the property of tasks which is executed in a wireless sensor network area. In this paper, the requirements satisfying real-time in sensor operating systems are analyzed and based on this, a system is designed and implemented. In addition, the proposed mechanisms are confirmed by several verification methods, and the efficiency of the performance and the satisfaction of those requirements for real-time are verified by simulation.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.177-179
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• 2006

This paper presents an analysis architecture of embedded operating systems for wireless sensor network. Wireless multi-hop sensor networks use battery-operated computing and sensing device. We expect sensor networks to be deployed in an ad hoc fashion, with very high energy constraints. These characteristics of multi-hop wireless sensor networks and applications motivate an operating system that is different from traditional embedded operating system. These days new wireless sensor network embedded operating system come out with some advances compared with previous ones. The analysis is focusing on understanding differences of dominant wireless sensor network OS, such as TinyOS 2.0 with TinyOS 1.x.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.242-250
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• 2007

Wireless sensor networks are subject to highly heterogeneous system requirements in terms of their functionality and performance due to their broad application areas. Though the heterogeneity hinders the opportunity of developing a single universal platform for sensor networks, efforts to provide uniform, inter-operable and scalable ones for sensor networks are still essential for the growth of the industry as well as their technological advance. As a part of our work to develop such a robust platform, this paper presents the software architecture for sensor nodes with focus on our sensor node operating system and its configuration methodology. Addressing principle issues in its design space which includes programming, execution, task scheduling and software layer models, our architecture is highly reconfigurable with respect to system resources and functional requirements and also highly efficient in supporting multi-threading under small system resources.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.13-20
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• 2008

Sensor network consists of a large number of sensor node distributed in the environment being sensed and controlled. The resource-constrained sensor nodes tend to have various and heterogeneous architecture. Thus, it is important to make its software environment platform-independent and reprogrammable. In this paper, we present BeeVM, a Java operating system designed for sensor networks. BeeVM offers a platform-independent Java programming environment with its efficiently executable file format and a set of class APIs for basic operating functions, sensing and wireless networking. BeeVM's high-level native interface and layered network subsystem allow complex program for sensor network to be short and readable. Our platform has been ported on two currently popular hardware platforms and we show its effectiveness through the evaluation of a simple application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2127-2133
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• 2010

In this paper, we proposed an architecture for supporting sensor transparency in sensor node operating systems, design the standard APIs (Application Programming Interfaces) and sensor device abstraction to provide the sensor transparency and implemented the sensor transparency in the TinyOS, the most well known sensor node operating system. With the proposed sensor node operating system which can support the sensor transparency, application developers can develop the target applications independent to each sensor device by using the standard APIs provided by the sensor node operating system and the sensor device manufacturers also can develop sensor device drivers by using the standard hardware interfaces and HAL (Hardware Adaptation Layer) interfaces independent to the specific hardware platform of sensor nodes.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.1
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• pp.37-48
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• 2011

Sensor networks monitor the environment, collect sensed data, and relay the data back to a collection point. Although sensor nodes have very limited hardware resources, they require an operating system that can provide efficient resource management and various application environments. In addition, the wireless sensor networks require the code update previously deployed to patch bugs in program and to improve performance of kernel service routines and application programs. This paper presents EPRCU (Easy to Perform Remote Code Update), a new operating system for wireless sensor nodes, which has enhanced functionalities to perform remote code update. To achieve an efficient code update, the EPRCU provides dynamic memory allocation and program memory management. It supports the event-driven kernel, which uses priority-based scheduling with the application of aging techniques. Therefore, the proposed operating system is not only easy to perform wireless communication with the remote code update but also suitable for various sensor network applications.

• Journal of Welding and Joining
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• v.11 no.3
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• pp.22-33
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• 1993

Arc sensor is indispensable to arc welding robot systems for compensating the joint misalignment such as mismatch of the workpiece, ill-conditioned positioner and thermal deformation during welding. Furthermore, the amount of these mismatches cannot be preivously expected, and changes from time to time. There are many kinds of seam trackers for correcting the welding path of the robot, where non-contact type sensors arc prevalently used in arc welding robot systems. In this study, an arc sensor was developed for GMA and FCA welding robot system. Since the arc sensor uses the arc characteristics during welding, the operating principle of the arc sensor must be adjusted according to the welding condition. Especially in GMA welding with the $CO_{2}$ shielding gas, the welding arc is not stable because of the short circuit and non-axial globular transfer mode of the molten droplet. In this study, the 2nd order least square curve fitting algorithm was adopted and the applicability of this algorithm was investigated for robot welding systems. For easy usage of the arc sensor, the operating parameters for arc sensor were limited to eight which can be easily determined by the operator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3423-3438
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• 2014

In recent years, wearable sensor devices are reshaping the way people live, work, and play. A wearable sensor device is a computer that is subsumed into the personal space of the user, and is always on, and always accessible. Therefore, among the most salient aspects of a wearable sensor device should be a small form factor, long battery lifetime, and real-time characteristics. Thereby, sophisticated applications of a wearable sensor device use real-time operating systems to guarantee real-time deadlines. The deterministic multi-dimensional task scheduling algorithms are implemented on ARC (Actual Remote Control) with relatively limited hardware resources. ARC is a wearable wristwatch-type remote controller; it can also serve as a universal remote control, for various wearable sensor devices. In the proposed algorithms, there is no limit on the maximum number of task priorities, and the memory requirement can be dramatically reduced. Furthermore, regardless of the number of tasks, the complexity of the time and space of the proposed algorithms is O(1). A valuable contribution of this work is to guarantee real-time deadlines for wearable sensor devices.