• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.175-185
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• 2005

The scheduling methods of the distributed real-time systems have been proposed. However, they have some weak points. They did not schedule both sporadic and periodic tasks and messages at the same time or did not consider the end-to-end constraints such as precedence relations between sporadic tasks. This means that system scheduling must guarantee the constraints of practical systems and be applicable to them. This paper proposes a new scheduling method that can be applied to more practical model of distributed real-time systems. System model consists of sporadic and periodic tasks with precedence relations and sporadic and periodic messages and has end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2350-2364
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• 2014

This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1441-1452
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• 2015

This paper proposes a new Hybrid Particle Swarm Optimization (HPSO) method that integrates the Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) techniques. The proposed method is applied to solve Economic Dispatch(ED) problems considering prohibited operating zones, ramp rate limits, capacity limits and power balance constraints. In the proposed HPSO method, the best features of both EP and PSO are exploited, and it is capable of finding the most optimal solution for the non-linear optimization problems. For validating the proposed method, it has been tested on the standard three, six, fifteen and twenty unit test systems. The numerical results show that the proposed HPSO method is well suitable for solving non-linear economic dispatch problems, and it outperforms the EP, PSO and other modern metaheuristic optimization methods reported in the recent literatures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4950-4966
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• 2015

Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1072-1078
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• 2008

In this paper, we propose an efficient superposition coding multiplexing(SCM) method based on power allocation in descending order for fading broadcast channels in which per-user minimum and maximum rate constraints are considered in order to maximize the transmission effectiveness. It consists of three steps as follows. In the first step, a user group is selected to maximize the number of users with whom a transmitter can communicate instantaneously. In the second step, per-user power allocation for each user is done in descending order of transmit power by determining a maximum allowable interference power from all subsequent interfering users in order to guarantee its corresponding minimum rate, and then a residual power is calculated. The final step is performed if some power remains even after the second step. In this step, additional power allocation is performed up to the maximum transmit power to provide the maximum rate to the corresponding user, again in ascending order, starting from the last user in descending order. But, this method does not require power reallocation to subsequent users because tentative power allocation in the second step has been performed in descending order to guarantee the minimum rate for each user, taking into account the maximum allowable interference power from all the subsequent users. Therefore, the proposed method gets more efficient in term of computational complexity when per-user minimum as well as maximum rate constraints exist, especially as the number of users increases.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.747-752
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• 2004

Researches about scheduling of the distributed real-time systems have been proposed. However, they have some weak points, not scheduling both sporadic and periodic tasks and messages or being unable to guaranteeing the end-to-end constraints due to omitting precedence relations between sporadic tasks. So this paper proposes a new scheduling method for distributed real-time systems consisting of sporadic and periodic tasks with precedence relations and sporadic and periodic messages, guaranteeing end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic (RM) scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.793-796
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• 1996

This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

• Korean Journal of Optics and Photonics
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• v.12 no.2
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• pp.109-114
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• 2001

Optical system has some optical and mechanical constraints. The constraints should be preserved in optimization of optical system. For the purpose, the constraints are combined with the merit function by using Lagrange's undetermined multipliers. We propose an active optimization control by using the fact that the errors of constraints are corrected with higher priority than the other errors of the merit function. In this control, the errors which have large contribution to the merit function are converted into constraints. At that time, if the errors are corrected at once, the optimization will be unstable because of their non-linearity. Hence we introduce a target rate which represents a fraction of error to be corrected, and the errors are corrected progressively. An optimization program was developed on the bases of the proposed active control, and applied to design a photographic lens system. By using the active control, we could get better results compared with conventional damped least squares method. ethod.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.509-516
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• 2011

This paper studies a novel method to find the profit-maximizing Nash Equilibriums in allocating generation quantities with consideration of ramp-rates under competitive market environment. Each GenCo in a market participates in a game to maximize its profit through competitions and play a game with bidding strategies. In order to find the Nash equilibriums it is necessary to search the feasible combinations of GenCos' strategies which satisfy every participant's profit and no one wants various constraints. During the procedure to find Nash equilibriums, the payoff matrix can be simplified as eliminating the dominated strategies. in each time interval. Because of the ramp-rate, generator's physically or technically limits to increase or decrease outputs in its range, it can restrict the number of bidding strategies of each generator at the next stage. So in this paper, we found the Nash Equilibriums for multi-stage generation allocation game considering the ramp-rate limits of generators. In the case studies, we analyzed the generation allocation game for a 12-hour multi-stage and compared it with the results of dynamic economic dispatch. Both of the two cases were considered generator's ramp-rate effects.

• IE interfaces
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• v.13 no.1
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• pp.110-119
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• 2000

Resource-constrained project scheduling is to allocate limited resources to activities to optimize certain objective functions and to determine a start time for each activity in the project such that precedence constraints and resource requirements are satisfied. This study suggests a multi-project scheduling model which can level work loads, make the most of production capacity and restrain the delay of delivery by developing a heuristic algorithm which minimizes the project completion time and maximizes the load rate under resource constraints.