• Journal of the Korea Society of Computer and Information
• /
• v.26 no.10
• /
• pp.27-35
• /
• 2021

Local search has been used to solve various combinatorial optimization problems. One of the most important factors in local search is the method of generating a neighbor solution. In this paper, we propose neighbor generation strategies of local search for permutation-based combinatorial optimization, and compare the performance of each strategies targeting the traveling salesman problem. In this paper, we propose a total of 10 neighbor generation strategies. Basically, we propose 4 new strategies such as Rotation in addition to the 4 strategies such as Swap which have been widely used in the past. In addition, there are Combined1 and Combined2, which are made by combining basic neighbor generation strategies. The experiment was performed by applying the basic local search, but changing only the neighbor generation strategy. As a result of the experiment, it was confirmed that the performance difference is large according to the neighbor generation strategy, and also confirmed that the performance of Combined2 is the best. In addition, it was confirmed that Combined2 shows better performance than the existing local search methods.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.69-76
• /
• 2022

The traveling salesman problem(TSP) is one of the most famous combinatorial optimization problem. So far, many metaheuristic search algorithms have been proposed to solve the problem, and one of them is local search. One of the very important factors in local search is neighbor generation method, and random-based neighbor generation methods such as inversion have been mainly used. This paper proposes 4 new greedy-based neighbor generation methods. Three of them are based on greedy insertion heuristic which insert selected cities one by one into the current best position. The other one is based on greedy rotation. The proposed methods are applied to first-choice hill-climbing search and simulated annealing which are representative local search algorithms. Through the experiment, we confirmed that the proposed greedy-based methods outperform the existing random-based methods. In addition, we confirmed that some greedy-based methods are superior to the existing local search methods.

• International journal of advanced smart convergence
• /
• v.10 no.1
• /
• pp.56-61
• /
• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.6 no.1
• /
• pp.83-90
• /
• 2010

DTNs (Delay Tolerant Networks) refer to the networks that can support data transmission in the extreme networking situations such as continuous delay and no connectivity between ends. DTMNs (Delay Tolerant Networks) are a specific range of DTNs, and its chief considerations in the process of message delivery in the routing protocol are the transmission delay, improvement of reliability, and reduction of network loading. This article proposes a new LCN (Largest Common Neighbor) routing algorism to improve Spray and Wait routing protocol that prevents the generation of unnecessary packets in a network by letting mobile nodes limit the number of copies of their messages to all nodes to L. Since higher L is distributed to nodes with directivity to the destination node and the maximum number of common neighbor nodes among the mobile nodes based on the directivity information of each node and the maximum number of common neighbor nodes, more efficient node transmission can be realized. In order to verify this proposed algorism, DTN simulator was designed by using ONE simulator. According to the result of this simulation, the suggested algorism can reduce average delay and unnecessary message generation.

• Journal of applied mathematics & informatics
• /
• v.25 no.1_2
• /
• pp.455-470
• /
• 2007

In phylogenetic tree construction the neighbor-joining algorithm is the most well known method which constructs a trivalent tree from a pairwise distance data measured by DNA sequences. The core part of the algorithm is its cherry picking criterion based on the tree structure of each quartet. We give a generalized version of the criterion based on the exact box model of quartets, known as the tight span of a metric. We also show by experiment why neighbor-joining and the quartet consistency count method give similar performance.

• Communications of the Korean Mathematical Society
• /
• v.25 no.1
• /
• pp.149-160
• /
• 2010

Among the distance based algorithms in phylogenetic tree reconstruction, the neighbor-joining algorithm has been a widely used and effective method. We propose a new algorithm which counts the number of consistent quartets for cherry picking with tie breaking. We show that the success rate of the new algorithm is almost equal to that of neighbor-joining. This gives an explanation of the qualitative nature of neighbor-joining and that of dissimilarity maps from DNA sequence data. Moreover, the new algorithm always reconstructs correct trees from quartet consistent dissimilarity maps.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.6
• /
• pp.1462-1470
• /
• 2013

This paper proposes an SWAD-KNH(Sybil & Wormhole Attack Detection using Key, Neighbor list and Hop count) technique which consists of an SWAD(Sybil & Wormhole Attack Detection) module detecting an Worm attack and a KGDC(Key Generation and Distribution based on Cluster) module generating and an sense node key and a Group key by the cluster and distributing them. The KGDC module generates a group key and an sense node key by using an ECDH algorithm, a hash function, and a key-chain technique and distributes them safely. An SWAD module strengthens the detection of an Sybil attack by accomplishing 2-step key acknowledgement procedure and detects a Wormhole attack by using the number of the common neighbor nodes and hop counts of an source and destination node. As the result of the SWAD-KNH technique shows an Sybil attack detection rate is 91.2% and its average FPR 3.82%, a Wormhole attack detection rate is 90%, and its average FPR 4.64%, Sybil and wormhole attack detection rate and its reliability are improved.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1545-1549
• /
• 2005

According as computer is supplied in a lot of homes and offices and Internet use increases, various service based on the Internet. Including wireless PDA in the future, many devices such as Internet telephone, TV, refrigerator and oven will be connected on the Internet and Internet address exhaustion will be raised to serious problem gradually. Today, the IPv4 address exhaustion problem has been solved partially using NAT (Network Address Translation) however, the transition to next Generation Internet will be accelerated because of advantages such as mobility, security service, QoS, and abundant IP addresses. In IPv6, all hosts are designed to create and set their address automatically without manager's intervention using Neighbor Discovery Protocol. But, when an IPv6 host sets its address automatically, there are serious security vulnerabilities. In this paper, we analysis security vulnerabilities in auto-configuration and provide security requirements for secure auto-configuration.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37C no.10
• /
• pp.888-893
• /
• 2012

Quality of Service (QoS) provisioning is an important issue in the design of next generation wireless network. In visible light communication (VLC) networks, link switching is a solution to maintain or improve the quality of communication. In this paper, we propose a novel link switching scheme using the location of mobile nodes (MNs). The current serving transmitter uses location history of the MN to find out which neighbor transmitter the MN is approaching. This neighbor transmitter is chosen to inform the MN as the next serving transmitter. The simulation results show that our proposed scheme gains better performance than non-predictive link switching scheme.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.3
• /
• pp.527-533
• /
• 2018

Recently, the device-to-device (D2D) communication has been conceived as the key technology for the next-generation mobile communication systems. The neighbor discovery in which the nearby users are found, is essential for the proper operation of the D2D communication. In this paper, we propose new neighbor discovery scheme based on deep learning technology which has gained a lot of attention recently. In the proposed scheme, the neighboring users can be found using the uplink pilot transmission of users only, unlike conventional neighbor discovery schemes in which direct pilot communication among users is required, such that the signaling overhead can be greatly reduced in our proposed scheme. Moreover, the neighbors with different proximity can also be classified accordingly which enables more accurate neighbor discovery compared to the conventional schemes. The performance of our proposed scheme is verified through the tensorflow-based computer simulations.