Youngjae Kim

A Bioinspired Fair Resource-Allocation Algorithm for TDMA-Based Distributed Sensor Networks for IoT

Many studies on distributed resource-allocation algorithms have been conducted recently because of the increasing number of network nodes and the rapidly changing network environments in the Internet of Things (IoT). In this paper, we propose the multihop DESYNC algorithm, which is a bioinspired Time Division Multiple Access- (TDMA-) based distributed resource-allocation scheme for distributed sensor networks. We define a detailed frame structure for the proposed multihop DESYNC algorithm and a firing message, which acts as a reference for resource allocation. In addition, operating procedures for resource allocation and collision detection avoidance under multihop DESYNC are explained. Simulations show that multihop DESYNC effectively resolves the hidden-node problem and that it fairly shares resources among nearby nodes in multihop networks. Moreover, it achieves better performance than the CSMA/CA algorithm in terms of channel reuse gain and average throughput.

A study on the impact of e-sports participation by students with mental retardation on their self-confidence and social skills

The purpose of this study is to find out the effect of e-sports participation on self-confidence and social development of mentally retarded students. To collect the data, retarded male students between and old were tested. They attend a special-education school located in Ha- am, young- i and they too part in the test for times. The test is about the e-sports(FIFA) and during wee s, from January th to February th, the five students too it for hours. before the five students participated in the e-sports, they had the self-confidence and social development tests and wees later they had the same tests again. According to the results of this participation, statistically, there was no effect of e-sports participation for mentally retarded students in their self-confidence and social development. However, there are some drawbacks first, there were only participants and among them only were capable to complete the questionnaire. Second, seven wees were not over analysed this case. y the way, the observation results of their behavioral changes are lie the followings with the personal characteristics, the results of the questionnaire, and the period of the participation. First of all, according to the personal characteristics of each retarded student, their preferences in the e-sports were different respectively. Thus, due to these dissimilar preferences, there was a difference in their results of confidence measurement. Second, there was no correlation between e-sports participation and social development. Based on the content and the interview of a specially trained teacher, reported that the participation of e-sports had a positive effect on the social development of mentally retarded students. On the contrary, based on the results of this case, participating e-sports itself had no effect on social development, However, the meeting during the e-sports lie an interaction to cooperated in games, or an competitive experience in on-line has an influence on social development.

Assessing destination image via social network analysis: the case of the “Coastal Uncorked Wine and Food Festival”

ABSTRACT Using social network analysis (SNA), this case study examines the image of a unique festival in a well-established tourist destination on the East coast of the United State of America, the Myrtle Beach area of South Carolina. SNA emphasizes the importance of constructing interconnectedness among concepts and knowledge networks in respondents’ minds. The technique visualizes complicated perception of tourists in a most simple but scientific way. Using concept maps and degree centralities derived from SNA, as well as dendrograms, this study provides insights on wine and food festival in Myrtle Beach Area. Together with cluster analysis, the SNA suggests unique contributions to the understanding of tourist behaviour in tourism destination research.

Mobility Load Balancing Method for Self-Organizing Wireless Networks Inspired by Synchronization and Matching With Preferences

Mobility load balancing (MLB) aims to resolve the mismatch between the distribution of network resources and the traffic demands. In this paper, we identify two key policies that characterize jointly an MLB method and propose algorithms for them to stabilize a network and increase the resource efficiency of a network. We adopt the synchronization model observed in nature to devise the first policy called a load assignment policy that determines the amount of loads tradable among cells. We design the second policy called a target selection policy by using the matching theory with preferences to determine the optimal pairs of user equipment (UE) and their new serving cells when the UE in an overloaded cell need to be handed over to its neighboring cells. Through mathematical analysis, we show the stability and the optimality of the proposed MLB method. We also show through simulation studies that the proposed method can distribute loads among cells more evenly than the conventional methods, which increases the total network throughput and the quality of service provided to UE.