• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.1-9
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• 2015

Recently, cognitive radio technology has been spotlighted for the efficient use of limited frequency technology. The most important part of CR is to protect the incumbent user's communications. Therefore, CR user should be sensing the currently using channel and another hopping channel for sudden appearance of the Incumbent User. In this paper, we propose the cooperative channel sensing to protect the IU considering each CR user's remained power and sensing-zone, sense the spectrum bands in a fairly distributed manner and share the results among the users within respective sensing zone. Sensing scheme including inband sensing and outband sensing is utilized. The inband sensing is in charge of current using channel scanning while the outband sensing mainly cares about other channels. The performance results by computer simulations show that our sensing scheduling scheme reduces the number of sensing nodes and saves energy need to channel sensing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.41-49
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• 2009

A crucial issue in deploying wireless sensor networks is to perform a sensing task in an area of interest in an energy-efficient manner since sensor nodes have limited energy Power. The most practical solution to solve this problem is to use a node wake-up scheduling protocol that some sensor nodes stay active to provide sensing service, while the others are inactive for conserving their energy In this paper, we present a simple wake-up scheduling protocol, which can maintain sensing coverage required by applications and yet increase network lifetime by turning off some redundant nodes. In order to do this, we use the concept of a weighted average distance. A node decides whether it is active or inactive based on the weighted average distance. The proposed protocol allows sensor nodes to sleep dynamically while satisfying the required sensing coverage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3302-3320
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• 2014

An allocation of sensing and reporting times is proposed to improve the sensing performance by scheduling them in an efficient way for cognitive radio networks with cluster-based cooperative spectrum sensing. In the conventional cooperative sensing scheme, all secondary users (SUs) detect the primary user (PU) signal to check the availability of the spectrum during a fixed sensing time slot. The sensing results from the SUs are reported to cluster heads (CHs) during the reporting time slots of the SUs and the CHs forward them to a fusion center (FC) during the reporting time slots of the CHs through the common control channels for the global decision, respectively. However, the delivery of the local decision from SUs and CHs to a CH and FC requires a time which does not contribute to the performance of spectrum sensing and system throughput. In this paper, a super-allocation technique, which merges reporting time slots of SUs and CHs to sensing time slots of SUs by re-scheduling the reporting time slots, has been proposed to sense the spectrum more accurately. In this regard, SUs in each cluster can obtain a longer sensing duration depending on their reporting order and their clusters except for the first SU belonged to the first cluster. The proposed scheme, therefore, can achieve better sensing performance under -28 dB to -10 dB environments and will thus reduce reporting overhead.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.484-493
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• 2009

For the flexible frequency utilization, cognitive radio technique has been prominently considered. The most important requirement in cognitive radio networks is to protect the communications of primary users. Spectrum sensing task by secondary users should be seriously considered in cognitive radio networks, since the spectrum sensing process makes their current quality of service worse. In this paper, we propose the channel sensing scheduling method that keeps the requirements for protecting the primary and guarantee the secondary user's quality of service as possible. The quality of service of secondary user is analyzed in terms of packet delay and loss while the protection-requirements in terms of sensing interval and sensing time predefined. In numerical analysis, we can get appropriate parameters which guarantee QoS in various environment. And simulation results show that this method can improve the performance, delay and the number of transmitted packets against consecutive sensing method.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.542-543
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• 2005

• Journal of Sensor Science and Technology
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• v.22 no.4
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• pp.268-275
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• 2013

Efficient energy management becomes a critical design issue for complex WSN (Wireless Sensor Network). Most of complex WSN employ the sleep mode to reduce the energy dissipation. However, it should cause the reduction of sensing coverage. This paper presents new wake-up algorithm for reducing energy consumption in complex WSN. The proposed wake-up algorithm is devised using geometric probability. It determined which node will be waked-up among the nodes having overlapped sensing coverage. The only one sensor node will be waked-up and it is ready to sense the event occurred uniformly. The simulation results show that the lifetime is increased by 15% and the sensing coverage is increased by 20% compared to the other scheduling methods. Consequently, the proposed wake-up algorithm can eliminate the power dissipation in the overlapped sensing coverage. Thus, it can be applicable for the various WSN suffering from the limited power supply.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.10
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• pp.708-714
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• 2014

Wireless sensor networks (WSNs) generally consist of densely deployed sensor nodes that depend on batteries for energy. Having a large number of densely deployed sensor nodes causes energy waste and high redundancy in sensor data transmissions. The problems of power limitation and high redundancy in sensing coverage can be solved by appropriate scheduling of node activity among sensor nodes. In this paper, we propose a cellular automata based node scheduling algorithm for prolonging network lifetime with a balance of energy savings among nodes while achieving high coverage quality. Based on a cellular automata framework, we propose a new mathematical model for the node scheduling algorithm. The proposed algorithm uses local interaction based on environmental state signaling for making scheduling decisions. We analyze the system behavior and derive steady states of the proposed system. Simulation results show that the proposed algorithm outperforms existing protocols by providing energy balance with significant energy savings while maintaining sensing coverage quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.364-370
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• 2010

In this paper, we propose a cooperative channel sensing scheme in the presence of feedback errors. Accurate local sensing results may not directly be applied to cooperative sensing due to feedback errors. We consider the cooperative channel sensing that utilizes local sensing results in good feedback channel condition. Finally, simulation results show that the proposed scheme can maximize the detection probability while guaranteeing desired false alarm probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5805-5825
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• 2019

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1423-1435
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• 2010

Building wireless sensor networks requires a constituting sensor node to consider the following limited hardware resources: a small battery lifetime limiting available power supply for the sensor node, a low-power microprocessor with a low-performance computing capability, and scarce memory resources. Despite such limited hardware resources of the sensor node, the sensor node platform needs to activate real-time sensing, guarantee the real-time processing of sensing data, and exchange data between individual sensor nodes concurrently. Therefore, in this paper, we propose an energy-efficient real-time task scheduling technique for battery-powered wireless sensor nodes. The proposed energy-efficient task scheduling technique controls the microprocessor's operating frequency and reduces the power consumption of a task by exploiting the slack time of the task when the actual execution time of the task can be less than its worst case execution time. The outcomes from experiments showed that the proposed scheduling technique yielded efficient performance in terms of guaranteeing the completion of real-time tasks within their deadlines and aiming to provide low power consumption.