• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.65-73
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• 2017

The fifth generation(5G) of wireless networks will connect not only smart phone but also unimaginable things. Therefore, 5G cellular network is facing the soaring traffic demand of numerous user devices. To solve this problem, a huge amount of 5G base stations will need to be installed. The base station positioning problem is an NP-hard problem that does not know how long it will take to solve the problem. Because, it can not find an answer other than to check the number of all cases. In this paper, to solve the NP hard problem, we compare the tabu search and the genetic algorithm using real maps for optimal cell planning. We also perform Monte Carlo simulations to study the performance of the Tabu search and Genetic algorithm for 5G cell planning. As a results, Tabu search required 2.95 times less computation time than Genetic algorithm and showed accuracy difference of 2dBm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.570-573
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• 1996

The evaluation test for the operation of rotary type surface mounters which consist of the reel axis, the index table and the X-Y table, has been performed by comparing the new method with the old one in only fields. Because the problem seeking for the optimal operation of rotary type surface mounters, is NP complete, it is almost impossible to get the optimal solutions of large problems. This paper deals with a dynamic network modeling, which can reduce the effort, the cost, and the time used for the performance test of rotary type surface mounters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.649-651
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• 2017

A clustering problem is one of the organizational problems to improve the network lifetime and scalability in wireless ad-hoc networks. This problem is a difficult combinatorial optimization problem associated with the design and operation of these networks. In this paper, we propose an efficient clustering algorithm to maximize the network lifetime and consider scalability in wireless ad-hoc networks. The clustering problem is known to be NP-hard. We thus solve the problem by using optimization approaches that are able to efficiently obtain high quality solutions within a reasonable time for a large size network. The proposed algorithm selects clusterheads and configures clusters by considering both nodes' power and the clustering cost. We evaluate this performance through some experiments in terms of nodes' transmission energy. Simulation results indicate that the proposed algorithm performs much better than the existing algorithms.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.319-326
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• 2004

To help network intrusion detection systems(NIDSs) keep up with the demands of today's networks, that we the increasing network throughput and amount of attacks, a radical new approach in hardware and software system architecture is required. In this paper, we propose a Network Processor(NP) based In-Line mode NIDS that supports the packet payload inspection detecting the malicious behaviors, as well as the packet filtering and the traffic metering. In particular, we separate the filtering and metering functions from the deep packet inspection function using two-level searching scheme, thus the complicated and time-consuming operation of the deep packet inspection function does not hinder or flop the basic operations of the In-line mode system. From a proto-type NP-based NIDS implemented at a PC platform with an x86 processor running Linux, two Gigabit Ethernet ports, and 2.5Gbps Agere PayloadPlus(APP) NP solution, the experiment results show that our proposed scheme can reliably filter and meter the full traffic of two gigabit ports at the first level even though it can inspect the packet payload up to 320 Mbps in real-time at the second level, which can be compared to the performance of general-purpose processor based Inspection. However, the simulation results show that the deep packet searching is also possible up to 2Gbps in wire speed when we adopt 10Gbps APP solution.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.247-257
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• 2005

Generally, the network topology design problem is characterized as a kind of NP-hard combinatorial optimization problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size. In this paper, we propose the efficient approach with two phase that is comprised of evolutionary computation approach based on Prufer number(PN), which can efficiently represent the spanning tree, and a heuristic method considering 2-connectivity, to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability: firstly, to find the spanning tree, genetic algorithm that is the most widely known type of evolutionary computation approach, is used; secondly, a heuristic method is employed, in order to search the optimal network topology based on the spanning tree obtained in the first Phase, considering 2-connectivity. Lastly, the performance of our approach is provided from the results of numerical examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.68-82
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• 2011

Wireless mesh networks (WMNs) provide high-speed backbone networks without any wired cable. Many researchers have tried to increase network throughput by using multi-channel and multi-radio interfaces. A multi-radio multi-channel WMN requires channel assignment algorithm to decide the number of channels needed for each link. Since the channel assignment affects routing and interference directly, it is a critical component for enhancing network performance. However, the optimal channel assignment is known as a NP complete problem. For high performance, most of previous works assign channels in a centralized manner but they are limited in being applied for dynamic network environments. In this paper, we propose a simple flow estimation algorithm and a hybrid channel assignment algorithm. Our flow estimation algorithm obtains aggregated flow rate information between routers by packet sampling, thereby achieving high scalability. Our hybrid channel assignment algorithm initially assigns channels in a centralized manner first, and runs in a distributed manner to adjust channel assignment when notable traffic changes are detected. This approach provides high scalability and high performance compared with existing algorithms, and they are confirmed through extensive performance evaluations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.87-94
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• 2019

A wireless sensor network is emerging technology and intelligent wireless communication paradigm that is dynamically aware of its surrounding environment. It is also able to respond to it in order to achieve reliable and efficient communication. The dynamical cognition capability and environmental adaptability rely on organizing dynamical networks effectively. However, optimally clustering the cognitive wireless sensor networks is an NP-complete problem. The objective of this paper is to develop an optimal sensor network design for maximizing the performance. This proposed Ranking Artificial Bee Colony (RABC) is developed based on Artificial Bee Colony (ABC) with ranking strategy. The ranking strategy can make the much better solutions by combining the best solutions so far and add these solutions in the solution population when applying ABC. RABC is designed to adapt to topological changes to any network graph in a time. We can minimize the total energy dissipation of sensors to prolong the lifetime of a network to balance the energy consumption of all nodes with robust optimal solution. Simulation results show that the performance of our proposed RABC is better than those of previous methods (LEACH, LEACH-C, and etc.) in wireless sensor networks. Our proposed method is the best for the 100 node-network example when the Sink node is centrally located.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.181-188
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• 2005

Chinese Postman Problem (CPP) is a problem that finds a shortest tour traversing all edges or arcs at least once in a given network. The Chinese Postman Problem on Mixed networks (MCPP) is a Practical generalization of the classical CPP and it has many real-world applications. The MCPP has been shown to be NP-complete. In this paper, we transform a mixed network into a symmetric network using virtual arcs that are shortest paths by Floyd's algorithm. With the transformed network, we propose a Genetic Algorithm (GA) that converges to a near optimal solution quickly by a multi-directional search technique. We study the chromosome structure used in the GA and it consists of a path string and an encoding string. An encoding method, a decoding method, and some genetic operators that are needed when the MCPP is solved using the Proposed GA are studied. . In addition, two scaling methods are used in proposed GA. We compare the performance of the GA with an existing Modified MDXED2 algorithm (Pearn et al. , 1995) In the simulation results, the proposed method is better than the existing methods in case the network has many edges, the Power Law scaling method is better than the Logarithmic scaling method.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.493-501
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• 2016

In-network storage is an effective technique for avoiding network congestion and reducing power consumption in continuous data collection in wireless sensor networks. In recent years, network coding based storage design has been proposed as a means to achieving ubiquitous access that permits any query to be satisfied by a few random (nearby) storage nodes. To maintain data consistency in continuous data collection applications, the readings of a sensor over time must be sent to the same set of storage nodes. In this paper, we present an efficient approach to updating data at storage nodes to maintain data consistency at the storage nodes without decoding out the old data and re-encoding with new data. We studied a transmission strategy that identifies a set of storage nodes for each source sensor that minimizes the transmission cost and achieves ubiquitous access by transmitting sparsely using the sparse matrix theory. We demonstrate that the problem of minimizing the cost of transmission with coding is NP-hard. We present an approximation algorithm based on regarding every storage node with memory size B as B tiny nodes that can store only one packet. We analyzed the approximation ratio of the proposed approximation solution, and compared the performance of the proposed coding approach with other coding schemes presented in the literature. The simulation results confirm that significant performance improvement can be achieved with the proposed transmission strategy.

• 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.