• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.6
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• pp.1101-1112
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• 2011

The Multiuser Eigenmode Transmission (MET) has generated significant interests in literature due to its optimal performance in linear precoding systems. The MET can simultaneously transmit several spatial multiplexing eigenmodes to multiple users which significantly enhance the system performance. The maximum number of users that can be served simultaneously is limited due to the constraints on the number antennas, and thus an appropriate user selection is critical to the MET system. Various algorithms have been developed in previous works such as the enumerative search algorithm. However, the high complexities of these algorithms impede their applications in practice. In this paper, motivated by the necessity of an efficient and effective user selection algorithm, a low complexity recursive user selection algorithm is proposed for the MET system. In addition, the fairness of the MET system is improved by using the combination of the proposed user selection algorithm and the adaptive Proportional Fair Scheduling (PFS) algorithm. Extensive simulations are implemented to verify the efficiency and effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.720-726
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• 2009

There are coexisting various kinds of data in the large scale database system, the maintenance problem of freshness of data is emerging important issue that provide correctness and usefulness information to users. Most solution of this problem depends on how execute effectively required refreshing query within timely time. In this paper, we propose the refreshing scheduling algorithm to retain the freshness of data and fairness of starvation of requested refresh queries. Our algorithm recompute a rate of goal refreshing a every period to assign execution time of requested refreshing query so that we can keep the freshness and fairness of data by using proposed algorithm. We implement the web sites to showing the results of refreshing process of dynamic and semi-dynamic and static data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1492-1512
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• 2011

Due to multiple hops, mobility and time-varying channel, supporting delay sensitive real-time traffic in wireless local area network-based (WLAN) mesh networks is a challenging task. In particular for real-time traffic subject to medium access control (MAC) layer control overhead, such as preamble, carrier sense waiting time and the random backoff period, the performance of real-time flows will be degraded greatly. In order to support real-time traffic, an efficient adaptive packet scheduling (APS) scheme is proposed, which aims to improve the system performance by guaranteeing inter-class, intra-class service differentiation and adaptively adjusting the packet length. APS classifies incoming packets by the IEEE 802.11e access class and then queued into a suitable buffer queue. APS employs strict priority service discipline for resource allocation among different service classes to achieve inter-class fairness. By estimating the received signal to interference plus noise ratio (SINR) per bit and current link condition, APS is able to calculate the optimized packet length with bi-dimensional markov MAC model to improve system performance. To achieve the fairness of intra-class, APS also takes maximum tolerable packet delay, transmission requests, and average allocation transmission into consideration to allocate transmission opportunity to the corresponding traffic. Detailed simulation results and comparison with IEEE 802.11e enhanced distributed channel access (EDCA) scheme show that the proposed APS scheme is able to effectively provide inter-class and intra-class differentiate services and improve QoS for real-time traffic in terms of throughput, end-to-end delay, packet loss rate and fairness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11B
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• pp.1031-1037
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• 2003

A new scheduling scheme, which uses channel quality information of each flow in Bluetooth system of ad-hoc network for effective bandwidth assignment, has been proposed in this paper. By an effective bandwidth assignment, QoS (Quality of Service) could have been ensured in case of asymmetric data traffic, mixed data transmission, and congested data transmission in a specific channel. The scheduling algorithm determines channel weights using partial channel information of flows. Case studies conducted by NS-2 (Network Simulator 2) and Bluehoc simulator has been presented to show the effectiveness of the proposed scheduling scheme.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.9-16
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• 2006

This paper proposes a scheduling algorithm for efficiently processing multimedia pakcet services in OFDMA physical system of the future broadband wireless access networks. The scheduling algorithm uses wireless channel state estimation, and allocates transmission rates after deciding transmission ordering based on class and priority policy. As the result, the proposed scheduling algorithm offers maximum throughput and minimum jitter for realtime services, and fairness for non-realtime services. In simulation study, the proposed algorithm proves superior performances than traditional round robin method.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.692-702
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• 2012

Supporting quality of service (QoS) guarantees for diverse multimedia services are the primary concerns for WiMAX (IEEE 802.16) networks. A scheduling scheme that satisfies QoS requirements has become more important for wireless communications. We propose a downlink scheduling scheme called adaptive priority-based downlink scheduling (APDS) for providing QoS guarantees in IEEE 802.16 networks. APDS comprises two major components: Priority assignment and resource allocation. Different service-type connections primarily depend on their QoS requirements to adjust priority assignments and dispatch bandwidth resources dynamically. We consider both starvation avoidance and resource management. Simulation results show that our APDS methodology outperforms the representative scheduling approaches in QoS satisfaction and maintains fairness in starvation prevention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.613-619
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• 2012

The Long Term Evolution (LTE) system is already able to provide a background of variety services for mobile users with multimedia services such as audio, video, and data. In fact, the High Speed Packet Access plus (HSPA+) solution can greatly enhance bit rates on down-link. However, the supporting for multimedia applications with different QoS (Quality of Service) requirements is not devised yet. Hence, in this paper we propose an effective packet scheduling algorithm based on Proportional Fairness (PF) scheduling algorithms for the LTE. In this proposed packet scheduling scheme, we optimized instantaneous user data rates and the traffic class weight which prioritize user's packets. Finally, we evaluated and showed the performance of the proposed scheduling algorithm through simulations of multimedia traffics being transmitted to users over LTE links in a multi-cell environment.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.249-256
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• 2007

GPS(generalized processor sharing) is a fair scheduling scheme that guarantees fair distribution of resources in an instantaneous manner, while virtual clock pursues fairness in the sense of long-term. In this paper, we notice that the degree of memorylessness is the key difference of the two schemes, and propose a unified scheduling model that covers the whole spectrum of history-sensitiveness. In this model, each application's resource right is represented in a value called deposit, which is accumulated at a predefined rate and is consumed for services. The unused deposit, representing non-usage history, gives the application more opportunity to be scheduled, hence relatively enhancing its response time. Decay of the deposit means partial erase of the history and, by adjusting the decaying rate, the degree of history-sensitiveness is controlled. In the spectrum, the memoryless end corresponds GPS and the other end with full history corresponds virtual clock. And there exists a tradeoff between average delay and long-term fairness. We examine the properties of the model by analysis and simulation.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.1-7
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• 2021

In this paper, We focused the issue of creating a socially problematic nurse schedule. The nurse schedule should be prepared in consideration of three shifts, appropriate placement of experienced workers, the fairness of work assignment, and legal work standards. Because of the complex structure of the nurse schedule, which must reflect various requirements, in most hospitals, the nurse in charge writes it by hand with a lot of time and effort. This study attempted to automatically create an optimized nurse schedule based on legal labor standards and fairness. We developed an I/O Q-Learning algorithm-based model based on Python and Web Application for automatic nurse schedule. The model was trained to converge to 100 by creating an Fairness Indicator Score(FIS) that considers Labor Standards Act, Work equity, Work preference. Manual nurse schedules and this model are compared with FIS. This model showed a higher work equity index of 13.31 points, work preference index of 1.52 points, and FIS of 16.38 points. This study was able to automatically generate nurse schedule based on reinforcement Learning. In addition, as a result of creating the nurse schedule of E hospital using this model, it was possible to reduce the time required from 88 hours to 3 hours. If additional supplementation of FIS and reinforcement Learning techniques such as DQN, CNN, Monte Carlo Simulation and AlphaZero additionally utilize a more an optimized model can be developed.