• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권6호
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• pp.2504-2526
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• 2016

Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

• 한국콘텐츠학회논문지
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• 제5권3호
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• pp.193-199
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• 2005

휴리스틱 알고리즘 연구에 있어서 중요한 분야 중 하나가 강화와 다양화의 조화를 맞추는 문제이다. 개미 집단 시스템은 최근에 제안된 조합 최적화문제를 해결하기 위한 메타 휴리스틱 기법으로, 그리디 탐색과 긍정적 보상에 의한 접근법으로 순회 판매원 문제를 풀기 위해 처음으로 제안되었다. 본 논문에서는 기존 개미집단 시스템의 성능을 향상시키기 위해 강화 전략과 다양화 전략으로 나누어진 엘리트 전략을 통해 집단간 긍정적 부정적 상호작용을 수행하는 다중 집단 개미 모델을 제안한다. 그리고, 이 제안된 엘리트 전략에 의한 다중 집단 상호작용 개미 모델을 순회판매원문제에 적용해 보고 그 성능에 대해 기존 개미집단 시스템과 비교한다.

• 대한전자공학회논문지TC
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• 제40권12호
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• pp.71-82
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• 2003

본 논문은 real-time 어플리케이션들을 위한 보나 효과적이고 효율적으로 ant-like mobile agent들이 QoS metrics를 고려하여 네트워크상에서 목적지까지 가장 최적화된 route을 찾는 Ant 알고리듬을 바탕으로 한 QoS 라우팅 알고리듬에서의 route 선택 강화 계산방법을 제시한다. 시뮬레이션 결과 본 논문에서 제시하는 방법이 기존의 방법보다 delay jitter와 bandwidth를 우선으로 하는 real-time application에 대한 가장 최적화된 route을 보다 효과적이고 보다 네트워크 환경에 적응적으로 찾아내는 것을 확인하였다.

• Journal of Microbiology
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• 제40권3호
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• pp.205-210
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• 2002

To study interactions between $C_{4}$-dicarboxylic acid transport protein D and E$\sigma$$^{54}$ in the dctA promoter regulatory region, we used the challenge phage system. An ant＇-｀lac fusion was recombined onto the challenge phage, and this ant＇-｀lac fusion along with Pant and the R. meliloti dctA promoter regulatory region were cloned onto a plasmid. The plasmid bearing the ant＇-｀lac fusion was used as a reporter plasmid in a coupled transcription-translation system. Addition of purified $\sigma$$^{54}$ to the coupled system specifically repressed transcription of the plasmid-borne ant＇-｀lac fusion. When DCTD was added along with $\sigma$$^{54}$ to the coupled system, transcription of the ant＇-｀lac fusion was even further repressed, suggesting that DCTD may stabilize closed complexes between E$\sigma$$^{54}$ and the dctA promoter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3496-3514
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• 2015

One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.

• Industrial Engineering and Management Systems
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• 제4권2호
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• pp.184-191
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• 2005

In this article we study the feasibility of the Ant Colony Optimisation (ACO) algorithm for finding optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the ACO algorithm contains a large number of adjustable parameters. Thus we study the influence of the parameters on performance of ACO on the Kanban allocation problem, and identify the most important parameters.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.308-311
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• 2008

The ant colony optimization (ACO) is a metaheuristic inspired by the behavior of real ants. Recently, ACO has been widely used to solve the difficult combinatorial optimization problems. In this paper, we propose an ACO algorithm to solve the two disjoint paths problem with dual link cost structure (TDPDCP). We propose a dual pheromone structure and a procedure for solution construction which is appropriate for the TDPDCP. Computational comparisons with the state-of-the-arts algorithms are also provided.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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• pp.77-78
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• 2008

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

• ETRI Journal
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• 제30권1호
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• pp.129-140
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• 2008

In this paper, we propose a novel ant colony optimization (ACO)-based test scheduling method for testing network-on-chip (NoC)-based systems-on-chip (SoCs), on the assumption that the test platform, including specific methods and configurations such as test packet routing, generation, and absorption, is installed. The ACO metaheuristic model, inspired by the ant's foraging behavior, can autonomously find better results by exploring more solution space. The proposed method efficiently combines the rectangle packing method with ACO and improves the scheduling results by dynamically choosing the test-access-mechanism widths for cores and changing the testing orders. The power dissipation and variable test clock mode are also considered. Experimental results using ITC'02 benchmark circuits show that the proposed algorithm can efficiently reduce overall test time. Moreover, the computation time of the algorithm is less than a few seconds in most cases.

• Journal of Applied Biological Chemistry
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• 제44권3호
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• pp.140-142
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• 2001

Quantitative gas chromatographic method for determining the ant repellent activity of cineol, ${\alpha}$-terpineol, linalool, and piperitone which usually found in Chinese Prickly Ash Zanthoxylum piperitum DC. was developed. These monoterpenes showed higher ant repellent activities than DEET due perhaps to their volatility. Gas chromatographic method quantified the volatility of the four monoterpenes and DEET.