• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4372-4388
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• 2014

Robotic sensor network (RSN) contains mobile sensors and robots providing feasible solution for many multi-agent applications. One of the most critical issues in RSN and its application is how to effectively assign tasks. This paper presents a novel connectivity preserving hybrid task allocation strategy to answer the question particularly for RSN. Firstly, we model the task allocation in RSN to distinguish the discovering and allocating processes. Secondly, a fully distributed simple Task-oriented Unoccupied Neighbor Algorithm, named TUNA, is developed to allocate tasks with only partial view of the network topology. A connectivity controller is finally developed and integrated into the strategy to guarantee the global connectivity of entire RSN, which is critical to most RSN applications. The correctness, efficiency and scalability of TUNA are proved with both theoretical analysis and experimental simulations. The evaluation results show that TUNA can effectively assign tasks to mobile robots with the requirements of only a few messages and small movements of mobile agents.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.1-6
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• 2009

A Thinning algorithm is a very Important factor in order to recognize the character, figure, and drawing. Until comparatively lately, the thinning algorithm was proposed by various methods. In this paper, we ascertain the point at issue of ZS(Zhang and Suen), LW(Lu and Wang) and WHF(Wang, Hui and Fleming) algorithms that are the parallel thinning algorithms. The parallel thinning algorithm means the first processing doesn't have to influence to the second processing. ZS algorithm has a problem which loses pixels in slanting lines and LW algorithm doesn't have one pixel width in slanting lines. So I propose an advanced parallel thinning algorithm that connects the pixels each other and preserve the end point.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.637-644
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• 2020

VANET (Vehicular Ad Hoc Networks) is a network between vehicles and between vehicles and infrastructure. VANET-specific characteristics such as high mobility, movement limitation, and signal interference by obstacles make it difficult to provide stable VANET services. To solve this problem, this paper proposes a vehicle type-based priority clustering method that improves the existing bus-based clustering. The proposed algorithm constructs a cluster by evaluating the priority, link quality, and connectivity based on the vehicle type, expected communication lifetime, and link degree of neighbor nodes. It tries to simplify the process of selecting a cluster head and increase cluster coverage by utilizing a predetermined priority based on the type of vehicle. The proposed algorithm is expected to become the basis for activating various services by contributing to providing stable services in a connected car environment.