• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.203-214
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• 2005

The integration of 3G networks and WLANs as complementary has been begun to attract much attention in industry as well as academia. This topic is becoming a burning issue, and one of the key questions which it raises is how to support a seamless vertical handoff. This paper introduces a new network interface selection algorithm for energy-efficient vertical handoff in tightly coupled systems capable of supporting seamless handoff. Our proposed scheme, Wise Interface Selection (WISE) switches the active network interface, after taking into consideration the characteristics of the network interface cards and the current level of data traffic, with the cooperation of the mobile terminals and network. Network interface switching operates independently on both the downlink and the uplink for the purpose of energy conservation. We show through simulation that less energy is consumed with WISE than when only a 3G network or WLAN interface is used, resulting in a longer lifetime for the mobile terminals. In the case of TCP connections, additional throughput gain can also be obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1976-1985
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• 2015

The amount of packets in palyout buffer of video streaming receiver can be changed by network condition, and saturated and exhausted by the delay and jitter. Especially, if the amount of incoming video traffic exceeds the maximum allowed playout buffer, buffer overflow problem can be generated. It makes the deterioration of video image and the discontinuity of playout by skip phenomenon. Also, if the incoming packets are delayed by network confusion, the stop phenomenon of video image is made by buffering due to buffer underflow problem. To solve these problems, this paper proposes the video streaming receiver with token bucket scheme which automatically establishes the important parameters like token generation rate r and bucket maximum capacity c adapting to the pattern of video packets. The simulation results using network simulator-2 (NS-2) and joint scalable video model (JSVM) show that the proposed token bucket scheme with automatic establishment parameter provides better performance than the existing token bucket scheme with manual establishment parameter in terms of the generation number of overflow and underflow, packer loss rate, and peak signal to noise ratio (PSNR) in three test video sequences.

• Journal of KIISE:Information Networking
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• v.27 no.3
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• pp.301-314
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• 2000

As the number of World Wide Web (Web) users grows, Web traffic continues to increase at an exponential rate. Currently, Web traffic is one of the major components of Internet traffic. Also, high bandwodth usage due to Web traffic is observed during peak periods while leaving bandwidth usage idle during off-peak periods. One of the solutions to reduce Web traffic and speed up Web access is through the use of Web caching. Unfortunately, Web caching has limitations for reducing network bandwidth usage during peak periods. In this paper, we focus our attention on the use of a prefetching algorithm for reducing bandwidth during peak periods by using off-peak period bandwidth. We propose a statistical, batch, proxy-side prefetching scheme that improves cache hit rate while only requiring a small amount of storage. Web objects that were accessed many times in previous 24 hours but would be expired in the next 24 hours, are selected and prefetched in our scheme. We present simulation results based on Web proxy and show that this prefetching algorithm can reduce peak time bandwidth using off-peak bandwidth.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.9-15
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• 2014

In this paper, We propose a block reallocation algorithm for reducing network traffic in Hadoop cluster. The scheduler of Hadoop cluster receives a job from users. And the job is divided into multiple tasks assigned to nodes. At this time, the scheduler allocates the task to the node that satisfied data locality. If a task is assigned to the node that does not have the data(block) to be processed, the task is processed after the data transmission from another node. There is difference of workload among nodes because blocks in cluster have different access frequency. Therefore, the proposed algorithm relocates blocks according to the task allocation pattern of Hadoop scheduler. Eventually, workload of nodes are leveled, and the case of the task processing in a node that does not have the block to be processing is reduced. Thus, the network traffic of the cluster is also reduced. We evaluate the proposed block reallocation algorithm by a simulation. The simulation result shows maximum 23.3% reduction of network consumption than default delay scheduling for jobs processing.

• The Journal of Bigdata
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• v.8 no.1
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• pp.131-156
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• 2023

The traditional retail industry significantly changed over the past decade due to the mobile and online technologies. This change has been accompanied by a shift in consumer behavior regarding purchasing patterns. Despite the rise of online shopping, there are still specific categories of products, such as "Processed food" in Mongolia, for which traditional shopping remains the preferred purchase method. To prepare for the inevitable future of retail businesses, firms need to closely analyze the performance of their offline stores to plan their further actions in a new multi-channel environment. Retailers must integrate diverse channels into their operations to stay relevant and adjust to the shifting market. In this research, we have analyzed the performance data such as sales, profit, and amount of sales of offline stores by using clustering approach. From the clustering, we have found the several distinct insights by comparing the circumstances and performance of retail stores. For the certain retail stores, we have proposed three different strategies: a fulfillment hub store between online and offline channels, an experience store to elongate customers' time on the premises, and a merge between two non-related channels that could complement each other to increase traffic based on the store characteristics. With the proposed strategies, it may enhance the user experience and profit at the same time.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.625-634
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• 2003

More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.