• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.1
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• pp.1-9
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• 2010

In this paper we propose a scheduling algorithm for supporting Quality of Service(QoS) in IEEE 802.11e HCCA referred to as ASR-DRR and ASD-DRR, which aims at providing improved performance for the support of multimedia traffic. Although We identify the problem of the current IEEE 802.11e HCCA (Hybrid Coordination Function Controlled Channel Access) scheduler and its numerous variations, that the queue information cannot be notified to the Hybrid Coordinator (HC) timely, therefore the uplink delay lengthens unnecessarily. We suggests a simple solution and a couple of implementation practices, namely the Adaptive Scheduler with RTS/CTS (ASR) and Adaptive Scheduler with Data/Ack (ASD). They are both further elaborated to emulate the Deficit Round Robin (DRR) scheduler. They are also compared with existing exemplary schedulers through simulation, and shown to perform well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.775-785
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• 2008

We identify the problem of the current IEEE 802. lie HCCA (Hybrid Coordination Function Controlled Channel Access) scheduler and its numerous variations, that the queue information cannot be notified to the Hybrid Coordinator (HC) timely, therefore the uplink delay lengthens unnecessarily. We suggests a simple solution and a couple of implementation practices, namely the Adaptive Scheduler with RTS/CTS (ASR) and Adaptive Scheduler with Data/Ack (ASD). They are both further elaborated to emulate the Deficit Round Robin (DRB) scheduler. They are finally compared with existing exemplary schedulers through simulations, and shown to perform well.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.280-291
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• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.