• The KIPS Transactions:PartA
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• v.16A no.1
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• pp.35-42
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• 2009

This paper proposes a new coverage algorithm for intelligent robot. Many algorithms for improving the performance of coverage have been focused on minimizing the total coverage completion time. However, if one does not have enough time to finish the whole coverage, the optimal path could be different. To tackle this problem, we propose a new coverage algorithm, which we call MaxCoverage algorithm, for covering maximal area within the deadline. The MaxCoverage algorithm decides the navigation flow by greedy algorithm for Set Covering Problem. The experimental results show that the MaxCoverage algorithm performs better than other algorithms for random deadlines.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.61-69
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• 2010

An autonomous robot must have a global workspace map in order to cover the complete workspace. However, most previous coverage algorithms assume that they have a grid workspace map that is to be covered before running the task. For this reason, most coverage algorithms can not be applied to complete coverage tasks in unknown environments. An autonomous robot has to build a workspace map by itself for complete coverage in unknown environments. Thus, we propose a new DmaxCoverage algorithm that allows a robot to carry out a complete coverage task in unknown environments. This algorithm integrates a SLAM algorithm for simultaneous workspace map building. Experimentally, we verify that DmaxCoverage algorithm is more efficient than previous algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.848-850
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• 2014

Mobile Ad hoc Networks(MANET) is consist of node that has mobility, MANET build cluster formation for using energy efficient. In existing LEACH algorithm elect cluster head node in coverage area by distribution function. However, when the cluster head node, that elected by distribution function, is divided coverage area unevenly, the network can't consumption energy efficiency. To solve this problem, we proposed CSWC(Coverage Scheduling Weight-value Control) algorithm. When the coverage area is divided nonchalance, proposed algorithm increased number of hops, that determines coverage area, for balance coverage area. As the result proposed algorithm is set balance coverage area, the network consumption energy efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.116-119
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• 2015

In this paper we propose an algorithm for environment monitoring using multiple mobile sensor (MS) nodes. Our focus is on maximizing sensing coverage of a group of MS nodes for monitoring a phenomenon in an unknown and open area over time. In the proposed algorithm, MS nodes are iteratively relocated to new positions at which a higher sensing coverage can be obtained. We formulated an integer linear programming (ILP) optimization problem to find the optimal positions for MS nodes with the objective of coverage maximization. The performance evaluation was performed to confirm that the proposed algorithm can enable MS nodes to relocate to high interest positions, and obtain a maximum sensing coverage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.5
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• pp.323-325
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• 2014

The consensus algorithm has a faster convergence speed as the number of cooperating neighbors increases, but the information sharing delay in the wireless network increases due to access collisions as the number of cooperating neighbors increases. Therefore, there exists a tradeoff between these two performances according to node's coverage. In this paper, we present a method of coverage control that minimizes consensus time according to network scale.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.406-412
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• 2010

In this paper, we formally define the problem of maximizing the coverage of sensor deployment, which is the optimization problem appeared in real-world sensor deployment, and analyze the properties of its solution space. To solve the problem, we proposed novel genetic algorithms, and we could show their superiority through experiments. When applying genetic algorithms to maximum coverage sensor deployment, the most important issue is how we evaluate the given sensor deployment efficiently. We could resolve the difficulty by using Monte Carlo method. By regulating the number of generated samples in the Monte Carlo evaluation of genetic algorithms, we could also reduce the computing time significantly without loss of solution quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.611-619
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• 2005

The present paper proposes two different packet scheduling algorithms in the IEEE 802.16e type TDD-OFDMA downlink, which are the weighted fair scheduling(WFS) and the throughput guarantee scheduling(TGS). The performance of proposed scheduling algorithms are compared to some of conventional schedulers such as round robin(RR), proportional fair(PF), fast fair throughput(FFTH), and fair throughput(FH) in terms of service coverage, effective throughput and fairness at 64 kbps and 128 kbps minimum user throughput requirements. For a relatively smaller throughput(64 kbps) requirement, the proposed algorithms provide higher improvement in the number of users per sector within 95$\%$ service coverage while satisfying the lxEV-DV fairness criterion. For a relatively larger throughput(128 kbps) requirement, the proposed algorithms provide higher coverage enhancement while maintaining the same effective aggregate throughput over PF scheduler.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.63-71
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• 2014

This paper proposes an algorithm that forms the clusters on the basis of hop distance in order to improve the actor coverage and connectivity in the sink-based wireless sensor and actor networks. The proposed algorithm forms the clusters that are distributed evenly in the target area by electing the CHs(Cluster Heads) at regular hop intervals from a sink. The CHs are elected sequentially from the sink in order to ensure the connectivity between the sink and the actors that are located on the CHs. Additionally, the electing are achieved from the area of the higher rate of the sensors density in order to improve the actor coverage. The number of clusters that are created in the target area and the number of the actors that are placed on the positions of the CHs are reduced by forming the clusters with regular distribution and minimizing the overlap of them through the proposed algorithm. Simulations are performed to verify that the proposed algorithm constructs the actor network that is connected to the sink. Moreover, we shows that the proposed algorithm improves the actor coverage and, therefore, reduces the amount of the actors that will be deployed in the region by 9~20% compared to the IDSC algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.54-55
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• 2016

무선 센터 네트워크 환경과 이동성을 지원하는 MANET이 결합된 환경에서 센서 커버리지 최대화 문제는 해결해야 할 중요한 문제 중 하나이다. 이 문제를 해결하기 위해 기존 연구에서는 자가 조직의 방식으로 노드 이동에 대하여 자가 결정, 근접 노드 검색, 노드 이동의 단계를 수행하는 알고리즘이 제시되었다. 하지만 기존 연구의 방식으로는 이미 노드의 배치가 최적화된 상태에서는 효과적이지 않다는 문제점을 가지고 있다. 이 논문에서는 기존 MANET 센서 커버리지 최대화 알고리즘의 문제점을 상세히 분석하고, 이 문제점을 해결하기 위한 해결 방안을 제시한다. 문제점을 제시하기 위해 MANET 환경을 모의구성하고 성능 실험을 실시하였다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.243-250
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• 2008

The coverage algorithm based on Boustrophedon path has been known to be the most efficient in places without or less obstacles If the map of an environmental area thru SLAM algorithm can be obtainable. However, the efficiency of the coverage algorithm based on Boustrophedon path drops drastically when obstacles are complex. In this paper, we propose and implement a new algorithm, which we call Group-k, that efficiently handles the complex area. The Group-k algorithm groups the obstacles and prioritizes the covering sequences with complex rank of the groups. Implementation-based experiments show about 20% improved performance when applying the nor- algorithm, compared to the Boustrophedon path algorithm.