• Journal of Communications and Networks
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• v.10 no.3
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• pp.338-350
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• 2008

The differentiated services (DiffServ) is proposed to provide packet level service differentiations in a scalable manner. To provide an end-to-end service differentiation to users having a connection over multiple domains, as well as a flow marker, an intermediate marker is necessary at the edge routers, and it should not be operated at a flow level due to a scalability problem. Due to this operation requirement, the intermediate marker has a fairness problem among the transmission control protocol (TCP) flows since TCP flows have intrinsically unfair throughputs due to the TCP's congestion control algorithm. Moreover, it is very difficult to resolve this problem without individual flow state information such as round trip time (RTT) and sending rate of each flow. In this paper, to resolve this TCP fairness problem of an intermediate marker, we propose a fair scalable marker (FSM) as an intermediate marker which works with a source flow three color marker (sf-TCM) operating as a host source marker. The proposed fair scalable marker improves the fairness among the TCP flows with different RTTs without per-flow management. Through the simulations, we show that the FSM can improve TCP fairness as well as link utilization in multiple domain DiffServ networks.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.79-83
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• 2004

The purpose of ATM traffic management is to protect the network using minimum resources and guarantee the requred QoS and also it is desirable to provide fairness between input channels. In this paper, we propose the TBBM(threshold based buffer management) algorithm to improve fairness between input channels and utilization of ATM networks. TBBM algorithm controls output cell rate dynamically based on threshold. The result shows that the required bandwidth of the TBBM algorithm is 14.3% lower in audio traffic and 41.8% lower in video traffic than that of theoretically calculated equivalent capacity method. and also reveals that the TBBM algorithm provide improved CLR fairness between input channels

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.89-97
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• 2010

The most important concern in the internet service organizations in competitive market circumstances is to focus on formation and maintenance of continuous relationship with customers. The purpose of this study is to verify the effect of perception of the fairness - procedural fairness for recovery, interactional fairness, fairness for reward on customer's satisfaction and trust, behavior when the internet service company failed to service such as disclosure of personal information. This study aims to apply justice theories to service recovery. As a result, first, the customer's perceived justice had a significant effect on the customer satisfaction and trust in service recovery. Second, the customer's satisfaction positive effect on trust. Third, customer's satisfaction formed by service recovery had a effect on the customer's behavior such as continuous usage intention. Therefore, this study was reveal how the extent of justice perception felt by customers in the service recovery process, causes positive causation relationship which affect customer behavior intention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.878-887
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• 2007

In this paper, a fairness scheme is proposed that assigns different number of HS-PDSCH to the service user according to the received SIR of CPICH. Assigned channel number is determined by the SIR level. The highest SIR user gets the number of channels based on the SIR table and the remained channels are assigned to the other SIR users. This scheme can serve the similar maximum service throughput and higher fairness than MAX CIR packet scheduling algorithm. This scheme can also serve the higher service throughput than Proportional Fairness scheme.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.65-74
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• 2003

In this Paper, we propose a downlink service admission strategy that considers users QoS requirements by using a novel service quality prediction index for multi-service WCDMA mobile systems. The Proposed downlink service admission strategy is obtained by computing average received Power of each service, assuming a relative other-cell interference factor. With the proposed method we obtain a downlink service admission region where users of different services properly can be admitted. And adding the fairness at the proposed downiinh service admission strategy, we Propose another downlink service admission strategy. In the numerical examples, the downlink service admission region with fairness and the downlink service admission region without fairness of voice service and data services are obtained by proposed downlink service admission strategies, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1992-2008
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• 2018

Mobile opportunistic network is a kind of ad hoc networks, which implements the multi-hop routing communication with the help of contact opportunity brought about by the mobility of the nodes. It always uses opportunistic data transmission mode based on store-carry-forward to solve intermittent connect problem of link. Although many routing schemes have been proposed, most of them adopt the greedy transmission mode to pursue a higher delivery efficient, which result in unfairness extremely among nodes. While, this issue has not been paid enough attention up to now. In this paper, we analyzed the main factors that reflect fairness among nodes, modeled routing selection as a multiple attribute decision making problem, and proposed our Fairness-aware Routing Strategy, named FARS. To evaluate the performance of our FARS, extensive simulations and analysis have been done based on a real-life dataset and a synthetic dataset, respectively. The results show that, compared with other existing protocols, our FARS can greatly improve the fairness of the nodes when ensuring the overall delivery performance of the network.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.5
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• pp.892-906
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• 2021

This study explores the effects of providing information on the price fairness perception and intention of continuous use in an online fashion platform, given a price difference due to AI algorithm pricing. We investigated the moderating roles of price inequality (loss vs. gain) and technology insecurity. The experiments used four stimuli based on price inequality (loss vs. gain) and information provision (provided or not) on price inequality. We developed a mock website and offered a scenario on the product presentation based on an AI algorithm pricing. Participants in their 20s and 30s were randomly allocated to one of the stimuli. To test the hypotheses, a total of 257 responses were analyzed using Process Macro 3.4. According to the results, price fairness perception mediated between information provision and continuous use intention when consumers saw the price inequality as a gain. When the consumers perceived high technology insecurity, information provision affected the intention of continuous use mediated by price fairness perception.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.91-102
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• 2009

The average window size is most closely related to average throughput. In order to improve fairness, the proposed dropper tries to control the window size of each flow to equal level by intentional packet drop. Intentional packet drop is performed only to the flows that have been occupied bandwidth in a large amount. Because of intentional packet drop, this flow cut down its transmission rate to a half. Accordingly, somewhat capacity of core link comes into existence. And other flow can use this new capacity of this link. Hence other flows have more throughput than before. In this paper, we propose the TRC (Transmission Rate Control) Dropper improving the fairness between individual flows of aggregated sources on DiffServ network. It has the fairness improvement mechanism mentioned above paragraph.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.385-390
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• 2023

The purpose of this study is to identify the antecedents and consequences of perceived fairness of assessment in an online class, such as Google classroom. Based on an extensive literature review, a research model and research questions were designed. We found that the perceived interactivity of contents and social presence were found to be antecedents of perceived fairness of assessment. Further, perceived fairness of assessment was found to have a substantial influence on class satisfaction and achievement.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.200-214
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• 2024

Amid the flood of data, social network analysis is beneficial in searching for its hidden context and verifying several pieces of information. This can be used for detecting the spread model of infectious diseases, methods of preventing infectious diseases, mining of small groups and so forth. In addition, community detection is the most studied topic in social network analysis using graph analysis methods. The objective of this study is to examine signed attributed social networks and identify the maximal balanced cliques that are both absolute and fair. In the same vein, the purpose is to ensure fairness in complex networks, overcome the "information cocoon" bottleneck, and reduce the occurrence of "group polarization" in social networks. Meanwhile, an empirical study is presented in the experimental section, which uses the personal information of 77 employees of a research company and the trust relationships at the professional level between employees to mine some small groups with the possibility of "group polarization." Finally, the study provides suggestions for managers of the company to align and group new work teams in an organization.