• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.131-134
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• 1996

Application of machine learning to scheduling problems has focused on improving system performance based on opportunistic selection among multitudes of simple rules. This study proposes a new method of learning scheduling rules, which first establishes qualitatively meaningful criteria and quantitatively optimizes the use of them, a similar way as human scheduler accumulate their expertise. The weighting of these criteria is trained in response to the system states through simulation. To mimic human quantitative feelings, distributed fuzzy sets are used for assessing the system state. The proposed method was applied to job dispatching in a simulated FMS environment. The job-dispatching criteria used were the length of the processing time of a job and the situation of the next workstation. The results show that the proposed method can develop efficient and robust scheduling strategies, which can also provide understandable and usable know-hows to the human scheduler.

• Journal of Communications and Networks
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• 제5권3호
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• pp.230-239
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• 2003

In this paper, we propose a framework to study how to route packets efficiently in multipath communication networks. Two traffic congestion control techniques, namely, flow assignment and packet scheduling, have been investigated. The flow assignment mechanism defines an optimal splitting of data traffic on multiple disjoint paths. The resequencing delay and the usage of the resequencing buffer can be reduced significantly by properly scheduling the sending order of all packets, say, according to their expected arrival times at the destination. To illustrate our model, and without loss of generality, Gaussian distributed end-to-end path delays are used. Our analytical results show that the techniques are very effective in reducing the average end-to-end path delay, the average packet resequencing delay, and the average resequencing buffer occupancy for various path configurations. These promising results can form a basis for designing future adaptive multipath protocols.

• ETRI Journal
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• 제26권1호
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• pp.48-52
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• 2004

In this letter, we consider a new packet scheduling algorithm for an orthogonal frequency division multiplexing access/frequency division duplex (OFDMA/FDD)-based system, e.g., mobile broadband wireless access or high-speed portable internet systems, in which the radio resources of both time and frequency slots are dynamically shared by all users under a proper scheduling policy. Our design objective is to increase the number of non-realtime service (e.g., WWW) users that can be supported in the system, especially when the minimum bit rate requirement is imposed on them. The simulation results show that our proposed algorithm can provide a significant improvement in the average outage probability performance for the NRT service, i.e., significantly increasing the number of NRT users without much compromising of the cell throughput.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.289-291
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• 1998

This paper presents short-term hydro scheduling method for hydrothermal coordination by genetic algorithm. Hydro scheduling problem has many constraints with fixed final reservoir volume. In this paper, the difficult water balance constraints caused by hydraulic coupling satisfied throughout dynamic decoding method. Adaptive penalizing method was also proposed to handle the infeasible solutions that violate various constraints. The effectiveness of proposed method in this paper was examined through the case studies. Further studies for the validation of the hydro scheduling scheme obtained by genetic algorithm will be very appreciated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4349-4371
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• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4823-4843
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• 2017

In this paper, an improved utility-based cross-layer dynamic subcarrier allocation (DSA) algorithm is proposed for single carrier frequency division multiple access (SC-FDMA) system, which adopts adaptive service rate control (ASRC) to eliminate the service rate waste and improve the spectral efficiency in heterogeneous network including non-real-time traffic and real-time traffic. In this algorithm, furthermore, a first in first out (FIFO) queuing model with finite space is established on the cross-layer scheduling framework. Simulation results indicate that by taking the service rate constraint as the necessary condition for optimality, the ASRC algorithm can effectively eliminate the service rate waste without compromising the scheduling performance. Moreover, the ASRC algorithm is able to further improve the quality of service (QoS) performance and transmission throughput by contributing an attractive performance trade-off between real-time and non-real-time applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권5호
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• pp.691-708
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• 2010

An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

• 한국항해학회지
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• 제24권5호
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• pp.361-371
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• 2000

This paper treats a genetic algorithm for ship scheduling problem in set packing formulation. We newly devised a partition based representation of solution and compose initial population using a domain knowledge of problem which results in saving calculation cost. We established replacement strategy which makes each individual not to degenerate during evolutionary process and applied adaptive mutate operator to improve feasibility of individual. If offspring is feasible then an improve operator is applied to increase objective value without loss of feasibility. A computational experiment was carried out with real data and showed a useful result for a large size real world problem.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.747-749
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• 2000

A new scheduling algorithm called the Adaptive Weighted Round Robin with Delay Tolerance (AWRR/DT) is presented. The proposed scheme can reduce the average delay of non-real-time (NRT) class while maintaining the QoS of real-time (RT) classes. Our scheme can also reflect the traffic fluctuation of networks with a small processing burden.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4754-4773
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• 2018

In sensor medium access control (SMAC) protocol, sensor nodes can only access the channel in the scheduling and listening period. However, this fixed working method may generate data latency and high conflict. To solve those problems, scheduling duty in the original SMAC protocol is divided into multiple small scheduling duties (micro duty MD). By applying different micro-dispersed contention channel, sensor nodes can reduce the collision probability of the data and thereby save energy. Based on the given micro-duty, this paper presents an adaptive duty cycle (DC) and back-off algorithm, aiming at detecting the fixed duty cycle in SMAC protocol. According to the given buffer queue length, sensor nodes dynamically change the duty cycle. In the context of low duty cycle and low flow, fair binary exponential back-off (F-BEB) algorithm is applied to reduce data latency. In the context of high duty cycle and high flow, capture avoidance binary exponential back-off (CA-BEB) algorithm is used to further reduce the conflict probability for saving energy consumption. Based on the above two contexts, we propose an improved SMAC protocol, micro duty adaptive SMAC protocol (MDA-SMAC). Comparing the performance between MDA-SMAC protocol and SMAC protocol on the NS-2 simulation platform, the results show that, MDA-SMAC protocol performs better in terms of energy consumption, latency and effective throughput than SMAC protocol, especially in the condition of more crowded network traffic and more sensor nodes.