• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.365-370
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• 2007

Connected Dominating Set(CDS) has been used as a virtual backbone in wireless ad hoc networks by numerous routing and broadcast protocols. Although computing minimum CDS is known to be NP-hard, many protocols have been proposed to construct a sub-optimal CDS. However, these protocols are either too complicated, needing non- local information, not adaptive to topology changes, or fail to consider the difference of energy consumption for nodes in and outside of the CDS. In this paper, we present two Timer-based Energy-aware Connected Dominating Set Protocols(TECDS). The energy level at each node is taken into consideration when constructing the CDS. Our protocols are able to maintain and adjust the CDS when network topology is changed. The simulation results have shown that our protocols effectively construct energy-aware CDS with very competitive size and prolong the network operation under different level of nodal mobility.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.389-398
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• 2010

The Vehicle Routing and Scheduling Problem with Time Windows(VRSPTW) is to establish a delivery route of minimum cost satisfying the time constraints and capacity demands of many customers. The VRSPTW takes a long time to generate a solution because this is a NP-hard problem. To generate the nearest optimal solution within a reasonable time, we propose the heuristic by using an ACO(Ant Colony Optimization) with multi-cost functions. The multi-cost functions can generate a feasible initial-route by applying various weight values, such as distance, demand, angle and time window, to the cost factors when each ant evaluates the cost to move to the next customer node. Our experimental results show that our heuristic can generate the nearest optimal solution more efficiently than Solomon I1 heuristic or Hybrid heuristic applied by the opportunity time.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.819-833
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• 2005

Code size reduction is ever becoming more important for compilers targeting embedded processors because these processors are often severely limited by storage constraints and thus the reduced code size can have a positively significant Impact on their performance. Various code size reduction techniques have different motivations and a variety of application contexts utilizing special hardware features of their target processors. In this work, we propose a novel technique that fully utilizes a set of hardware instructions, called the multiple load/store (MLS), that are specially featured for reducing code size by minimizing the number of memory operations in the code. To take advantage of this feature, many microprocessors support the MLS instructions, whereas no existing compilers fully exploit the potential benefit of these instructions but only use them for some limited cases. This is mainly because optimizing memory accesses with MLS instructions for general cases is an NP-hard problem that necessitates complex assignments of registers and memory off-sets for variables in a stack frame. Our technique uses a couple of heuristics to efficiently handle this problem in a polynomial time bound.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.959-968
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• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1142-1147
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• 2015

As a method to increase the scalability and efficiency of wireless sensor networks, a scheme to construct networks hierarchically has received considerable attention among researchers. Researches on the methods to construct wireless networks hierarchically have been conducted focusing on how to select nodes such that they constitute a backbone network of wireless network. Nodes comprising the backbone network should be connected themselves and can cover other remaining nodes. A problem to find the minimum number of nodes which satisfy these conditions is known as the minimum connected dominating set (MCDS) problem. The MCDS problem is NP-hard, therefore there is no efficient algorithm which guarantee the optimal solutions for this problem at present. In this paper, we propose a novel multi-start local search algorithm to solve the MCDS problem efficiently. For the performance evaluation of the proposed method, we conduct extensive experiments and report the results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2303-2308
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• 2012

In this paper, we deal with the problem of scheduling parallel tasks with deadlines. Parallel tasks can be simultaneously executed on various machines and specially, we consider the malleable tasks, that is, the tasks whose execution time is given by a function of the number of machines on which they are executed. The goal of the problem is to maximize the throughput of tasks completed within their deadlines. This problem is well-known as NP-hard problem. Thus we will find an approximation algorithm, and its performance is compared with that of the optimal algorithm and analyzed by finding the approximation ratio. In particular, the algorithm has more resources, that is, more machines, than the optimal algorithm. This is called the resource augmentation analysis. We propose an algorithm to guarantee the approximation ratio of 3.67 using 1.5 times machines.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12B
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• pp.728-734
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• 2007

In this paper, we propose a GOSST(Grade Of Services Steiner minimum Tree) heuristic mechanism for the design of a physical multiple security grade network with minimum construction cost. On the network, each node can communicate with other nodes by its desiring security grade. Added to the existing network security methods, the preventing method from illegal physical access is necessary for more safe communication. To construct such network with minimum cost, the GOSST problem is applied. As the GOSST problem is a NP-Hard problem, a heuristic with reasonable complexity is necessary for a practical solution. In this research, to design the physical multiple security grade network with the minimum construction cost, the reformed our previous Distance Direct GOSST heuristic mechanism is proposed. The mechanism brings average 29.5% reduction in network construction cost in comparison with the experimental control G-MST.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.155-165
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• 2012

This paper suggests traveling salesman problem algorithm that have been unsolved problem with NP-Hard. The proposed algorithm is a heuristic with edge-swap method. The classical method finds the initial solution starts with first node and visits to mostly adjacent nodes then decides the traveling path. This paper selects minimum weight edge for each nodes, then perform Min-Min method that start from minimum weight edge among the selected edges and Min-Max method that starts from maximum weight edges among it. Then we decide tie initial solution to minimum path length between Min-Min and Min-Max method. To get the final optimal solution, we apply previous two-opt to initial solution. Also, we suggest extended 3-opt and 4-opt additionally. For the 7 actual experimental data, this algorithm can be get the optimal solutions of state-of-the-art with fast and correct.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.44-52
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• 2008

This paper is on the enhancement of our heuristics for Grade Of Services Steiner Minimum Tree (GOSST) problem that can apply to the design of communication networks offering manifold grade of services in multimedia communication area. GOSST problem known as one of NP-Hard problems asks for a network topology meeting the G-Condition with minimum construction cost. In our prior researches, we proposed some heuristics for the problem. In this paper, we suggest a strategy of G-Condition scrutiny sequence to fortify our previous heuristics. In the experiment results, the ameliorated achieves 71.9% economy of execution times, 28.9% of required Steiner points and 1.1% of network construction costs.