• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.53-63
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• 2008

Reader collision may occur when neighboring RFID readers use the same channel at the same time. Especially when the readers are operated in dense mode, even though many channels are available, because of frequent reader collisions we can not guarantee the performance of RFID readers. Conventional solutions such as FH(Frequency Hopping) or LBT(Listen Before Talk) are not effective in this situation because they can not schedule RFID readers effectively when RFID readers are operated in multi-channel, dense reader mode, In this paper, we propose a new RFID reader anti-collision algorithm which employs LBT, random backoff before channel access, and probabilistic channel hopping at the same time. While LBT and Random backoff before channel access reduces collisions between competing readers, probabilistic channel hopping increases channel utilization by adaptively changing the hopping probability by reflecting the reader density and utilization. Simulation results shows that our algorithm outperforms conventional methods.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.493-501
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• 2007

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et at suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, the NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In NORA algorithm, EDF strategy is adopted in the optional scheduling. On the other hand, for the task system with 0/1 constraint, EDF_Scheduling may not be optimal in the sense that the total error is minimized. Furthermore, when the optional tasks are scheduled in the ascending order of their required processing times, NORA algorithm which EDF strategy is adopted may not produce minimum total error. Therefore, in this paper, an online algorithm is proposed to minimize total error for the imprecise task system with 0/1 constraint. Then, to compare the performance between the proposed algorithm and NORA algorithm, a series of experiments are performed. As a conseqence of the performance comparison between two algorithms, it has been concluded that the proposed algorithm can produce similar total error to NORA algorithm when the optional tasks are scheduled in the random order of their required processing times but, the proposed algorithm can produce less total error than NORA algorithm especially when the optional tasks are scheduled in the ascending order of their required processing times.

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.150-159
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• 1998

This paper described the recognition of the Off-line handwritten Hangul based on neural network using a feature extraction method. Features of Hangul can be extracted by a $5{\times}5$ window method which is the modified $3{\times}3$ mask method. These features are coded to binary patterns in order to use neural network's inputs efficiently. Hangul character is recognized by the consonant, the vertical vowel, and the horizontal vowel, separately. In order to verify the recognition rate, three different coding methods were used for neural networks. Three methods were the fixed-code method, the learned-code I method, and the learned-code II method. The result was shown that the learned-code II method was the best among three methods. The result of the learned-code II method was shown 100% recognition rate for the vertical vowel, 100% for the horizontal vowel, and 98.33% for the learned consonants and 93.75% for the new consonants.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.191-195
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• 2008

This paper proposes a technique for improving IEEE 802.11e EDCA's performance by dynamically adjusting each class's contention window size based on each class's traffic amount. For providing differentiated service differently from 802.11, 802.11e EDCA maintains four classes each of which specifies different static minimum and maximum contention window sizes. Since the initial window sites significantly affect the 802.11e performance, several window adjustment schemes have been proposed. One of the schemes known as CWminAS (CWmin Adaptation Scheme) dynamically and synchronously determines the four windows' site based on the periodically measured collision rate. This method, however, can lower the send probability of high priority classes since it can't differentiate their collisions from those of low priority classes, leading to the channel underutilization. For solving this problem, we propose ACATICT(Adaptive Contention-window Adjustment Technique based on Individual Class Traffic) algorithm which adapts each class window size based on each individual collision rate rather than one average collision rate. Our simulation experiments show that ACATICT achieves better utilization by around 10% at maximum.