• KIPS Transactions on Computer and Communication Systems
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• v.2 no.9
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• pp.405-412
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• 2013

Current web has evolved to a mashed-up format according to the change of the implementation and usage patterns. Web services and user experiences have improved, however, security threats are also increased as the web contents that are not yet verified combine together. To mitigate the threats incurred as an adverse effect of the web development, we need to check security on the combined web contents. In this paper, we propose a scheduling method to detect malicious web pages not only inside but also outside through extended links for secure operation of a web site. The scheduling method considers several aspects of each page including connection popularity, suspiciousness, and check elapse time to make a decision on the order for security check on numerous web pages connected with links. We verified the effectiveness of the security check complying with the scheduling method that uses the priority given to each page.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.21-39
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• 2006

This paper presents a mixed linear and integer goal programming (GP) model to aid in strategic planning and scheduling of guard soldiers. The proposed model is a general-purpose model, hence can be used to produce an optimal schedule with respect to any user-provided combination of guard post objectives and soldier preferences. We extensively test the usefulness of the model on a real-life dataset from a guard post in the ROK Army with using three objectives set by the guard post and three preferences provided by individual solders. Numerical results and analysis from these experiments show that the proposed guard scheduling model efficiently as well as effectively generates an optimal guard schedule and can also be used for an optimal revision of any existing schedule. In summary, these illustrate that the proposed model can be practically used for optimal planning and scheduling of guard soldiers in guard posts.

• The Journal of Korean Association of Computer Education
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• v.11 no.3
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• pp.91-99
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• 2008

In recent years, wireless networks have been widely deployed and the use of mobile devices has been popularized. As a result, mobile devices are increasingly considered as a resource of the Grid However, there are some problems such as unstable wireless communication and disconnection of mobile devices caused by movement in Mobile Grid Therefore, a scheduling method allocating jobs to the mobile devices should progressively deal with this problem The existing scheduling methods in Mobile Grid have mainly focused on the connection time of mobile devices. The connection time of mobile devices shows typically a regular pattern according to a user's living environments such as vacation/class in school, weekday/weekend in work, and so on. In this paper, we analyze statistics information for the utilization patterns of mobile devices and propose global and local scheduling methods for Mobile Grid, based on the analyzed utilization patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3876-3895
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• 2014

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn-Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5S
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• pp.1620-1628
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• 2000

Existing internet auction systems have adopted the form which gives a win to the auction bidder who proposes the top bid price for the goods posted on the auction board. But they haven't been satisfying the automatical one-step processing for user's convenience because they must require continuous care of user for bidding and checking as well as neglecting the convenience of user interface while participating in the electronic bidding system. The AuctionBot system of Michigan Univ. is known as the representative internet auction system. It has merit allowing the various kids of bidding. But it does not support automatic a process which can replaces what user has to do using an agent. To improve this kind of user interface, we propose an automatic bidding price strategy algorithm which composes the auction system using agent and design for auto-bidding system using agent so that I can replace user's bidding activity. This mechanism gives an auction system the efficient bidding price strategy.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.38-46
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• 2011

The OPRoS (Open Platform for Robotic Service) framework provides uniform operating environment for service robots. As an OPRoS-based service robot has to support real-time as well as non-real-time applications, application of Windows NT kernel based operating system can be restrictive. On the other hand, various benefits such as rich library and device support and abundant developer pool can be enjoyed when service robots are built on Windows NT. The paper presents a user-mode component scheduler of OPRoS, which can provide near real-time scheduling service on Windows NT based on the restricted real-time features of Windows NT kernel. The component scheduler thread with the highest real-time priority in Windows NT system acquires CPU control. And then the component scheduler suspends and resumes each periodic component executors based on its priority and precedence dependency so that the component executors are scheduled in the preemptive manner. We show experiment analysis on the performance limitations of the proposed scheduling technique. The analysis and experimental results show that the proposed scheduler guarantees highly reliable timing down to the resolution of 10ms.

• Journal of The Korean Association of Information Education
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• v.4 no.2
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• pp.140-146
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• 2001

Scheduling strategy in the Education-on-Demand system should be designed to service the isochronous requests from several learners with single disk retrieval to improve the performance of the system. In this paper, the scheduling strategy which reduces the disk I/O and buffer consumption by utilizing the resources of the learner's system has been proposed. All the requests from the learner are not serviced from the server but forwarded to the learner's system which preserves the requested information. Therefore, the server can increase the throughput and reduces the initial latency time of the user. The proposed strategy has been compared to the conventional method by simulations and proved to be more efficient.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.398-403
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• 2008

Data broadcasting is a mechanism to transmit information to clients in simplex transmission environments. In this mechanism, server transmits to repeat all information to all users and users use a necessary data when the data is transmitted. Therefore users are waiting the necessary data until the data is transmitted. It is important to reduce user's waiting time. Server schedules the data to reduce waiting time. In this paper, we study efficient data scheduling algorithm. The result shows that the performance of the proposed method is increased 13 percent compared to the method considering only request frequency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3423-3438
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• 2014

In recent years, wearable sensor devices are reshaping the way people live, work, and play. A wearable sensor device is a computer that is subsumed into the personal space of the user, and is always on, and always accessible. Therefore, among the most salient aspects of a wearable sensor device should be a small form factor, long battery lifetime, and real-time characteristics. Thereby, sophisticated applications of a wearable sensor device use real-time operating systems to guarantee real-time deadlines. The deterministic multi-dimensional task scheduling algorithms are implemented on ARC (Actual Remote Control) with relatively limited hardware resources. ARC is a wearable wristwatch-type remote controller; it can also serve as a universal remote control, for various wearable sensor devices. In the proposed algorithms, there is no limit on the maximum number of task priorities, and the memory requirement can be dramatically reduced. Furthermore, regardless of the number of tasks, the complexity of the time and space of the proposed algorithms is O(1). A valuable contribution of this work is to guarantee real-time deadlines for wearable sensor devices.