• The KIPS Transactions:PartC
• /
• v.16C no.6
• /
• pp.783-790
• /
• 2009

The necessity of wireless sensor networks is increasing in the recent years. So many researches are studied in wireless sensor networks. The clustering algorithm provides an effective way to prolong the lifetime of the wireless sensor networks. The one-hop routing of LEACH algorithm is an inefficient way in the energy consumption of cluster-head, because it transmits a data to the BS(Base Station) with one-hop. On the other hand, other clustering algorithms transmit data to the BS with multi-hop, because the multi-hop transmission is an effective way. But the multi-hop routing of other clustering algorithms which transmits data to BS with multi-hop have a data bottleneck state problem. The unequal clustering algorithm solved a data bottleneck state problem by increasing the routing path. Most of the unequal clustering algorithms partition the nodes into clusters of unequal size, and clusters closer to the BS have small-size the those farther away from the BS. However, the energy consumption of cluster-head in unequal clustering algorithm is more increased than other clustering algorithms. In the thesis, I propose an energy efficient unequal clustering algorithm which decreases the energy consumption of cluster-head and solves the data bottleneck state problem. The basic idea is divided a three part. First of all I provide that the election of appropriate cluster-head. Next, I offer that the decision of cluster-size which consider the distance from the BS, the energy state of node and the number of neighborhood node. Finally, I provide that the election of assistant node which the transmit function substituted for cluster-head. As a result, the energy consumption of cluster-head is minimized, and the energy consumption of total network is minimized.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.1
• /
• pp.53-64
• /
• 2014

One of the major problems to forecast election, especially based on survey, is nonresponse. We may have different forecasting results depend on method of imputation. Handling nonresponse is more important in a survey about sensitive subject, such as presidential election. In this research, we consider a model based method of nonresponse imputation. A model based imputation method should be constructed based on assumption of nonresponse mechanism and may produce different results according to the nonresponse mechanism. An assumption of the nonresponse mechanism is very important precondition to forecast the accurate results. However, there is no exact way to verify assumption of the nonresponse mechanism. In this paper, we compared the accuracy of prediction and assumption of nonresponse mechanism based on the result of presidential election exit poll. We consider maximum likelihood estimation method based on EM algorithm to handle assumption of the model of nonresponse. We also consider modified within precinct error which Bautista (2007) proposed to compare the predict result.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.9
• /
• pp.795-802
• /
• 2002

We present a new dynamic routing scheme for multiple autonomous guided vehicles (AGVs) systems. There have been so many results concerned with scheduling and routing of multiple AGV systems; however, most of them are only applicable to systems with a small number of AGVs under a low degree of concurrency. With an increased number of AGVs in recent applications, these AGV systems are faced with another problem that has never been occurred in a system with a small number AGVs. This is the stop propagation problem. That is, if a leading AGV stops then all the following AGVs must stop to avoid any collision. In order to resolve this problem, we propose a nonstop preferential detour (NPD) algorithm which is a new dynamic routing scheme employing an election algorithm. For real time computation, we introduce two stage control scheme and propose a new path searching scheme, k-via shortest path scheme for an efficient dynamic routing algorithm. Finally, the proposed new dynamic routing scheme is illustrated by an example.

• Journal of KIISE:Information Networking
• /
• v.36 no.2
• /
• pp.98-107
• /
• 2009

In this paper, we propose a novel centralized energy-efficient clustering algorithm, called "MCCA : Max k-Cut based Clustering Algorithm for Wireless Sensor Networks." The algorithm does not use location information and constructs clusters via a distributive Max k-Cut based cluster-head election method, where only relative and approximate distance information with neighbor nodes is used and nodes, not having enough energy, are excluded for cluster-heads for a specific period. We show that the energy efficiency performance of MCCA is better than that of LEACH, EECS and similar to BCDCP's by simulation studies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.5
• /
• pp.415-422
• /
• 2017

Finding influential factors from given clustering result is a typical data science problem. Genetic Algorithm based method is proposed to derive influential factors and its performance is compared with two conventional methods, Classification and Regression Tree (CART) and Chi-Squared Automatic Interaction Detection (CHAID), by using Dunn's index measure. To extract the influential factors of preference towards political parties in South Korea, the vote result of $18^{th}$ presidential election and 'Demographic', 'Health and Welfare', 'Economic' and 'Business' related data were used. Based on the analysis, reverse engineering was implemented. Implementation of reverse engineering based approach for influential factor analysis can provide new set of influential variables which can present new insight towards the data mining field.

• International journal of advanced smart convergence
• /
• v.5 no.1
• /
• pp.66-72
• /
• 2016

In this paper, we proposed the clustering algorithm using fuzzy inference system for improving adaptability the cluster head selection of TEEN. The stochastic selection method cannot guarantee available of cluster head. Furthermore, because the formation of clusters is not optimized, the network lifetime is impeded. To improve this problem, we propose the algorithm that gathers attributes of sensor node to evaluate probability to be cluster head.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.587-590
• /
• 2019

This paper is about to improve the network life's reduction due to the deviation of sensor node and frequently change of network, the main problem of sensor network. The existing Scalable Topology Organization(STO)-based ZigBee Tree Topology Control Algorithm did not consider ways to consume power so the network lifetime is too short. Accordingly, per each round, electing a new parent node and consisting of the new network topology technique, The Cluster Header Selection, extending the network's overall lifetime. The OMNet++ Simulator yielded results from the existing STO Algorithm and the proposed Cluster Header Selection Technique in the same experimental environment, which resulted in an increase in overall network life by about 40% and an improvement of about 10% in performance in the remaining portion of the battery.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.10
• /
• pp.197-203
• /
• 2011

In this paper, a new cluster configuration process is proposed. The energy consumption of sensor nodes is reduced by configuring the initial setup process only once with keeping the initial cluster. Selecting the highest power consumed node of the member nodes within the cluster to the header of next round can distribute power consumption of all nodes in the cluster evenly. With this proposed way, the lifetime of the USN is increased by the reduced energy consumption of all nodes in the cluster. Also, evenly distributed power consumptions of sensors are designed to improve the energy hole problem. The effectiveness of the proposed algorithms is confirmed through simulations.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.6B
• /
• pp.342-349
• /
• 2007

Clustering protocol of Wireless sensor networks(WSNs) not only reducing the volume of inter-node communication by the nodes's data aggreation but also extending the nodes's sleep times by cluster head's TDMA-schedule coordination. In order to extend network lifetime of WSNs, we propose ECS algorithm to select cluster-head using three variables. It consists of initial and current energy of nodes, round information and total numbers which have been selected as cluster head until current round.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.4 no.2
• /
• pp.29-37
• /
• 2008

Clustering allows hierarchical structures to be built on the nodes and enables more efficient use of scarce resources, such as frequency spectrum, bandwidth, and energy in wireless sensor networks (WSNs). This paper proposes a hierarchical clustering algorithm called EEHC which is more energy efficient than existing algorithms for WSNs, It introduces region node selection as well as cluster head election based on the residual battery capacity of nodes to reduce the costs of managing sensor nodes and of the communication among them. The role of cluster heads or region nodes is rotated among nodes to achieve load balancing and extend the lifetime of every individual sensor node. To do this, EEHC clusters periodically to select cluster heads that are richer in residual energy level, compared to the other nodes, according to clustering policies from administrators. To prove the performance improvement of EEHC, the ns-2 simulator was used. The results show that it can reduce the energy and bandwidth consumption for organizing and managing WSNs comparing it with existing algorithms.