• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.137-142
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• 2021

Distance learning universities provide online course content. The main methods of providing class contents are on-demand and live-streaming. This means that students are not restricted by time or space. The advantage is that students can take the course anytime and anywhere. Therefore, unlike commuting students, there is no commuting time to the campus, and there is no natural process required to take classes. However, despite this convenient situation, the attendance rate and graduation rate of distance learning universities tend to be lower than that of commuting universities. Although the course environment is not the only factor, students cannot obtain a bachelor's degree unless they fulfill the graduation requirements. In both commuter and distance learning universities, taking classes is an important factor in earning credits. There are fewer time and space constraints for distance learning students than for commuting students. It is also easy for distance learning students to take classes at their own timing. There should be more ease of learning than for students who commute to school with restrictions. However, it is easier to take a course at a commuter university that conducts face-to-face classes. I thought that the reason for this was that commuting to school was a part of the process of taking classes for commuting students. Commuting to school was thought to increase the willingness and motivation to take classes. Therefore, I thought that the inconvenient constraints might encourage students to take the course. In this research, I focused on the act of commuting to school by students. These situations are also applied to the distance learning environment. The students have physical time constraints. To achieve this goal, I will implement a course restriction method that aims to promote the willingness and attitude of students. Therefore, in this paper, I have implemented a virtual school system called "virtual go to school (VG2S)" that reflects the actual route to school.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.36-44
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• 2014

Exploiting the energy-delay tradeoff for energy saving is critical for developing green wireless communication systems. In this paper, we investigate the delay-constrained energy-efficient packet transmission. We aim to minimize the energy consumption of multiple randomly arrived packets in an additive white Gaussian noise channel subject to individual packet delay constraints, by taking into account the practical on-off circuit power consumption at the transmitter. First, we consider the offline case, by assuming that the full packet arrival information is known a priori at the transmitter, and formulate the energy minimization problem as a non-convex optimization problem. By exploiting the specific problem structure, we propose an efficient scheduling algorithm to obtain the globally optimal solution. It is shown that the optimal solution consists of two types of scheduling intervals, namely "selected-off" and "always-on" intervals, which correspond to bits-per-joule energy efficiency maximization and "lazy scheduling" rate allocation, respectively. Next, we consider the practical online case where only causal packet arrival information is available. Inspired by the optimal offline solution, we propose a new online scheme. It is shown by simulations that the proposed online scheme has a comparable performance with the optimal offline one and outperforms the design without considering on-off circuit power as well as the other heuristically designed online schemes.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.52-59
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• 2008

This paper describes the secant method for solving the economic dispatch (ED) problem with generator constraints and transmission losses. The ED problem is an important optimization problem in the economic operation of a power system. The proposed algorithm involves selection of minimum and maximum incremental costs (lambda values) and then the evaluation of optimal lambda at required power demand is done by secant method. The proposed algorithm has been tested on a power system having 6, 15, and 40 generating units. Studies have been made on the proposed method to solve the ED problem by taking 120 and 200 units with generator constraints. Simulation results of the proposed approach were compared in terms of solution quality, convergence characteristics, and computation efficiency with conventional methods such as lambda iterative method, heuristic methods such as genetic algorithm, and meta-heuristic methods like particle swarm optimization. It is observed from different case studies that the proposed method provides qualitative solutions with less computational time compared to various methods available in the literature.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.334-345
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• 2010

In this paper, we study optimal tradeoffs of achievable throughput versus consumed power in wireless ad-hoc networks formed by a collection of multiple antenna nodes. Relying on adaptive modulation and/or dynamic channel coding rate allocation techniques for multiple antenna systems, we examine the maximization of throughput under power constraints as well as the minimization of transmission power under throughput constraints. In our examination, we also consider the impacts of enforcing quality of service requirements expressed in the form of channel coding block loss constraints. In order to properly model temporally correlated loss observed in fading wireless channels, we propose the use of finite-state Markov chains. Details of fading statistics of signal-to-interference-noise ratio, an important indicator of transmission quality, are presented. Further, we objectively inspect complexity versus accuracy tradeoff of solving our proposed optimization problems at a global as oppose to a local topology level. Our numerical simulations profile and compare the performance of a variety of scenarios for a number of sample network topologies.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.1-22
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• 2011

In this paper, we propose an adaptive genetic algorithm (aGA) approach for effectively solving the sequencing problem with precedence constraints (SPPC). For effective representation of the SPPC in the aGA approach, a new representation procedure, called the topological sort-based representation procedure, is used. The proposed aGA approach has an adaptive scheme using a fuzzy logic controller and adaptively regulates the rate of the crossover operator during the genetic search process. Experimental results using various types of the SPPC show that the proposed aGA approach outperforms conventional competing approaches. Finally the proposed aGA approach can be a good alternative for locating optimal solutions or sequences for various types of the SPPC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5191-5211
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• 2016

It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation networks. The present study proposes a QoS-driven multicast scheme for wireless networks in which the transmission rate and end-to-end delay are assumed to be bounded during a multiple multicast session. A distributed algorithm was used to identify a cost-efficient sub-graph between the source and destination which can satisfy QoS constraints of a multicast session. The model was then modified as to be applied for wireless networks in which satisfying interference constraints is the main challenge. A discrete power control scheme was also applied for the QoS-aware multicast model to accommodate the effect of transmission power level based on link capacity requirements. We also proposed random power allocation (RPA) and gradient power allocation (GPA) algorithms to efficient resource distribution each of which has different time complexity and optimality levels. Experimental results confirm that the proposed power allocation techniques decrease the number of unavailable links between intermediate nodes in the sub-graph and considerably increase the chance of finding an optimal solution.

• ETRI Journal
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• v.42 no.5
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• pp.700-711
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• 2020

Because of the rapid increase of mobile traffic, flexible broadband supportive unmanned aerial vehicle (UAV)-based 6G mobile networks using free space optical (FSO) links have been recently proposed. Considering the advancements made in UAVs, big data processing, and artificial intelligence precision control technologies, the formation of an additional wireless network based on UAV aerial platforms to assist the existing fixed base stations of the mobile radio access network is considered a highly viable option in the near future. In this paper, a combined time bound optimization scheme is proposed that can adaptively satisfy the control and communication time constraints as well as the processing time constraints in FSO-based 6G UAV aerial networks. The proposed scheme controls the relation between the number of data flows, input data rate, number of worker nodes considering the time bounds, and the errors that occur during communication and data processing. The simulation results show that the proposed scheme is very effective in satisfying the time constraints for UAV control and radio access network services, even when errors in communication and data processing may occur.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.198-209
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• 2007

This paper provides a thorough study on shared segment protection (SSP) for mesh communication networks in the complete routing information scenario, where the integer linear program (ILP) in [1] is extended such that the following two constraints are well addressed: (a) The restoration time constraint for each connection request, and (b) the switching/merging capacity constraint at each node. A novel approach, called SSP algorithm, is developed to reduce the extremely high computation complexity in solving the ILP formulation. Basically, our approach is to derive a good approximation on the parameters in the ILP by referring to the result of solving the corresponding shared path protection (SPP) problem. Thus, the design space can be significantly reduced by eliminating some edges in the graphs. We will show in the simulation that with our approach, the optimality can be achieved in most of the cases. To verify the proposed formulation and investigate the performance impairment in terms of average cost and success rate by the additional two constraints, extensive simulation work has been conducted on three network topologies, in which SPP and shared link protection (SLP) are implemented for comparison. We will demonstrate that the proposed SSP algorithm can effectively and efficiently solve the survivable routing problem with constraints on restoration time and switching/merging capability of each node. The comparison among the three protection types further verifies that SSP can yield significant advantages over SPP and SLP without taking much computation time.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.105-115
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• 2006

In this paper, we investigate the problem of minimizing average inventory costs subject to a fill rate constraint in a two-stage serial inventory model with a normally distributed demand. Fill rate is the fraction of demand that is satisfied immediately from on-hand inventory. We first find the lower bounds of base-stock levels in each node by using the exact base-stock level that satisfies a fill rate in a single node model proposed by Sobel. And then, we extensively analyze the system and show that the cost function is convex. Using such convexity and some other useful properties, we can easily find optimal base-stock levels numerically.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.248-257
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• 2005

In this paper, we develop design procedures for carrier tracking loop for orthogonal frequency division multiplexing (OFDM) systems or other systems of blocked data. In such communication systems, phase error measurements are made infrequent enough to invalidate the traditional loop design methodology which is based on analog loop design. We analyze the degradation in the OFDM schemes caused by the tracking loop and show how the performance is dependent on the rms phase error, where we distinguished between the effect of the variance in the average phase over the symbol and the effect of the phase change over the symbol. We derive the optimal tracking loop including optional delay in the loop caused by processing time. Our solution is general and includes arbitrary phase noise apd additive noise spectrums. In order to guarantee a well behaved solution, we have to check the design against margin constraints subject to uncertainties. In case the optimal loop does not meet the required margin constraints subjected to uncertainties, it is shown how to apply a method taken from control theory to find a controller. Alternatively, if we restrict the solution to first or second order loops, we give a simple loop design procedure which may be sufficient in many cases. Extensions of the method are shown for using both pilot symbols and data symbols in the OFDM receiver for phase tracking. We compare our results to other methods commonly used in OFDM receivers and we show that a large improvement can be gained.