• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.102-108
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• 2020

One of the key features of a mobile crowd-sensing (MCS) system is task allocation, which aims to recruit workers efficiently to carry out the tasks. Due to various constraints of the tasks (such as specific sensor requirement and a probabilistic guarantee of task completion) and workers heterogeneity, the task allocation become challenging. This assignment problem becomes more intractable because of the deadline of the tasks and a lot of possible task completion order or moving path of workers since a worker may perform multiple tasks and need to physically visit the tasks venues to complete the tasks. Therefore, in this paper, a hybrid search algorithm for task allocation called HST is proposed to address the problem, which employ a traveling salesman problem heuristic to find the task completion order. HST is developed based on the tabu search algorithm and exploits the premature convergence avoiding concepts from the genetic algorithm and simulated annealing. The experimental results verify that our proposed scheme outperforms the existing methods while satisfying given constraints.

• 한국정보처리학회논문지
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• 제4권7호
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• pp.1681-1693
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• 1997

분산 시스템에서 파일 할당 문제는 시스템의 운영비용을 최소화하기 위해 파일 및 그의 복제물의 최적 위치를 결정하는 것이다. 정적인 파일 할당 문제는 분산 시스템의 각 노드에서 특정 파일에 발생하는 질의 및 갱신에 관련된 비용이 일정하다는 가정에서 출발하고 있다. 그러나 실제로는 시간이 지남에 따라 질의 및 갱신 등에 관련된 매개변수들은 변하게 마련이다. 이 연구에서 다루고 있는 동적인 파일 할당 문제는 변화하는 매개변수들을 고려하고 있으며, 또한 시스템 내에 파일이 한 종류만 있는 경우뿐만 아니라 여러 종류가 있는 경우도 다루고 있다. 동적인 파일 할당 문제는 혼합 정수계획법으로 모형화 되었으며 문제 해결을 위해 Lagrange 함수를 이용한 분단탐색법(branch-and-bound method) 알고리즘이 개발되었다. 제시된 알고리즘은 포트란으로 프로그램화되었으며, 여러 종류의 문제 해결을 통하여 그의 유용성을 보여주고 있다.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.306-317
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• 2021

The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.3008-3028
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• 2022

In this paper, we investigate traffic scheduling for a delay-sensitive multi-hop relay network, and aim to minimize the priority-based end-to-end delay of different data packet via joint relay selection, subcarrier assignment, and power allocation. We first derive the priority-based end-to-end delay based on queueing theory, and then propose a two-step method to decompose the original optimization problem into two sub-problems. For the joint subcarrier assignment and power control problem, we utilize an efficient particle swarm optimization method to solve it. For the relay selection problem, we prove its convexity and use the standard Lagrange method to deal with it. The joint relay selection, subcarriers assignment and transmission power allocation problem for each hop can also be solved by an exhaustive search over a finite set defined by the relay sensor set and available subcarrier set. Simulation results show that both the proposed routing scheme and the resource allocation scheme can reduce the average end-to-end delay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권2호
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• pp.288-307
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• 2013

This paper formulates resource allocation for decode-and-forward (DF) relay assisted multi-cell orthogonal frequency division multiple (OFDM) networks as an optimization problem taking into account of inter-cell interference and users fairness. To maximize the transmit rate of system we propose a joint interference coordination, subcarrier and power allocation algorithm. To reduce the complexity, this semi-distributed algorithm divides the primal optimization into three sub-optimization problems, which transforms the mixed binary nonlinear programming problem (BNLP) into standard convex optimization problems. The first layer optimization problem is used to get the optimal subcarrier distribution index. The second is to solve the problem that how to allocate power optimally in a certain subcarrier distribution order. Based on the concept of equivalent channel gain (ECG) we transform the max-min function into standard closed expression. Subsequently, with the aid of dual decomposition, water-filling theorem and iterative power allocation algorithm the optimal solution of the original problem can be got with acceptable complexity. The third sub-problem considers dynamic co-channel interference caused by adjacent cells and redistributes resources to achieve the goal of maximizing system throughput. Finally, simulation results are provided to corroborate the proposed algorithm.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.191-194
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• 2003

Location-allocation problem is known as one of the important problem faced in Industrial Engineering and Operations Research fielde. There are many variations on this problem for different applications, however, most of them consider no obstacle existing. Since the location-allocation problem with obstacles is very complex and with many infeasible solutions, no direct method is effective to solve it. In this paper we propose a hybrid Genetic Algorithm (hGA) method for solving this problem. The proposed hGA is based on Lagrangian relaxation method and Dijkstra's shortest path algorithm. To enhance the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.

• Journal of Advanced Research in Ocean Engineering
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• 제1권2호
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• pp.94-105
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• 2015

In this study, a thruster allocation method of a deep-sea working vessel was proposed with the aims of producing the demanded generalized forces and moment for dynamic positioning while at the same time minimizing total power. For this, an optimization problem for thrust allocation was mathematically formulated with design variables, objective function, and constraints. The genetic algorithms (GA) was used to solve the formulated problem. The proposed method was applied to an example of finding optimal thrust allocation of the deep-sea working vessel having 5 thrusters. The result showed that the method could be used to determine better strategy for thruster allocation of the vessel as compared to existing study.

• ETRI Journal
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• 제36권6호
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• pp.960-967
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• 2014

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi-channel wireless multihop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems - flow control; next-hop routing; rate allocation and scheduling; power control; and channel allocation - and finally solved by a low-complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.

• Journal of Communications and Networks
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• 제11권2호
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• pp.157-165
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• 2009

In this paper, we investigate a dynamic spectrum sharing problem for the centralized uplink cognitive radio networks using orthogonal frequency division multiple access. We formulate a large-scale joint rate and power allocation as an optimization problem under quality of service constraint for secondary users and interference constraint for primary users. We also suggest admission control to nd a feasible solution to the optimization problem. To implement the resource allocation on a large-scale, we introduce a notion of using the conservative factors $\alpha$ and $\beta$ depending on the outage and violation probabilities. Since estimating instantaneous channel gains is costly and requires high complexity, the proposed algorithm pursues a practical and implementation-friendly resource allocation. Simulation results demonstrate that the large-scale joint rate and power allocation incurs a slight loss in system throughput over the instantaneous one, but it achieves lower complexity with less sensitivity to variations in shadowing statistics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5943-5962
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• 2017

A resource allocation algorithm based on simultaneous wireless information and power transfer (SWIPT) to maximize the system throughput is proposed in orthogonal frequency division multiplexing (OFDM) relay networks. The algorithm formulates the problem under the peak power constraints of the source and each subcarrier (SC), and the energy causality constraint of the relay. With the given SC allocation of the source, we give and prove the optimal propositions of the formulated problem. Then, the formulated problem could be decomposed into two separate throughput maximization sub-problems by setting the total power to transfer energy. Finally, several SC allocation schemes are proposed, which are energy priority scheme, information priority scheme, balanced allocation scheme and exhaustive scheme. The simulation results reveal that the energy priority scheme can significantly reduce computational complexity and achieve approximate performance with the exhaustive scheme.