• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.501-510
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• 2006

Software streaming allows the execution of stream-enabled software on desktop or portable computing devices like PC, PDA, laptop, cellular phone, etc., even while the transmission/streaming from the server may still be in progress. In this paper, we present an efficient streaming system called Software On-Demand(SOD) streaming system to transmit stream-enabled applications in addition to automatic installation of program registry, environment variables, configuration files, and related components. In particular, we design and implement a SOD system in Linux to provide the user with the instant look-and-click software execution environment such that software download and installation are internally proceeded in a completely user-transparent way. Therefore, the SOD system relieves the user from the tricky, failure-prone installation business. In addition, the software developer now obtains a new, powerful means to advertise and propagate their software products since the user can use software packages via user-friendly UI window or web browser by look-and-click interactive operation. In the paper, we also make a couple of SOD streaming experiments using a spectrum of popular softwares. Based on the analysis of the experiment results, we also propose two performance improvement schemes.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.699-708
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• 2002

Since various terminals and different networks get involved in playing of a multimedia presentation, the case that the presentation QoS at a destination should be different from the QoS of multimedia data at a source occurs frequently. For playing the multimedia presentation, the multimedia data at a source should be transcoded into the multimedia data satisfying the QoS required at the terminal. The problem of generating the transcoding path is that, for a given multimedia presentation, different transcoding paths depending the terminal and networks should be generated. That is, a fixed transcoding path cannot be applied to a multimedia presentation. Instead, whenever the terminal and network to play the presentation get determined, a proper transcoding path should be regenerated automatically. In this paper, the algorithm for generating the transcoding path and the method for checking the playability of the generated path are proposed. The generating algorithm adopted the technique of Context Free Grammar in describing the set of transcoding resources and a user's transcoding rules in order to utilize the well-known compiler techniques. For the playability check, a method of computing the transcoding time and the delay time between data units are proposed. Finally all the proposed methods were implemented in the stream engine, called Transcore and the presentation-authoring tool, called VIP, we had developed. And the test results with a sample scenario were presented at the last.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.1-13
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• 2009

Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.19-31
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• 2014

In this paper, a parallel backoff delay procedure on multiple IEEE 802.15.4 channels and a channel searching method considering the frequency spectrum of WiFi traffic are studied for IEEE 802.15.4 nodes to avoid the interference from WiFi traffic. In order to search the channels being occupied by WiFi traffic, we analyzed the methods measuring the powers of adjacent channels simultaneously, checking the duration of measured power levels greater than a threshold, and finding the same periodicity of sampled RSSI data as the beacon frame by signal processing. In an wireless channel overlapped with IEEE 802.11 network, the operation of CSMA-CA algorithm for IEEE 802.15.4 nodes is explained. A method to execute a parallel backoff procedure on multiples IEEE 802.15.4 channels by an IEEE 802.15.4 device is proposed with the description of its algorithm. When we analyze the data measured by the experimental system implemented with the proposed method, it is observed that medium access delay times increase at the same time in the associated IEEE 802.15.4 channels that are adjacent each other during the generation of WiFi traffic. A channel evaluation function to decide the interference from other traffic on an IEEE 802.15.4 channel is defined. A channel searching method considering the channel evaluations on the adjacent channels together is proposed in order to search the IEEE 802.15.4 channels interfered by WiFi, and the experimental results show that it correctly finds the channels interfered by WiFi traffic.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.53-59
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• 2016

Recently, huge stream data have been generated in real time from various applications such as wireless sensor networks, Internet of Things services, and social network services. For this reason, to develop an efficient method have become one of significant issues in order to discover useful information from such data by processing and analyzing them and employing the information for better decision making. Since stream data are generated continuously and rapidly, there is a need to deal with them through the minimum access. In addition, an appropriate method is required to analyze stream data in resource limited environments where fast processing with low power consumption is necessary. To address this issue, the sliding window model has been proposed and researched. Meanwhile, one of data mining techniques for finding meaningful information from huge data, pattern mining extracts such information in pattern forms. Frequency-based traditional pattern mining can process only binary databases and treats items in the databases with the same importance. As a result, frequent pattern mining has a disadvantage that cannot reflect characteristics of real databases although it has played an essential role in the data mining field. From this aspect, high utility pattern mining has suggested for discovering more meaningful information from non-binary databases with the consideration of the characteristics and relative importance of items. General high utility pattern mining methods for static databases, however, are not suitable for handling stream data. To address this issue, sliding window based high utility pattern mining has been proposed for finding significant information from stream data in resource limited environments by considering their characteristics and processing them efficiently. In this paper, we conduct various experiments with datasets for performance evaluation of sliding window based high utility pattern mining algorithms and analyze experimental results, through which we study their characteristics and direction of improvement.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.33-39
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• 2016

With recent advances in sensor technology, CMOS-based semiconductor devices and networking protocol, the areas for application of wireless sensor networks greatly expanded and diversified. Such diversification of uses for wireless sensor networks creates a multitude of beneficial possibilities for several industries. In the application of wireless sensor networks for monitoring systems' data transmission process from the sensor node to the sink node, transmission through multi-hop paths have been used. Also mobile sink techniques have been applied. However, high energy costs, unbalanced energy consumption of nodes and time gaps between the measured data values and the actual value have created a need for advancement. Therefore, this thesis proposes a new model which alleviates these problems. To reduce the communication costs due to frequent data exchange, a State Prediction Model has been developed to predict the situation of the peripheral node using a geographic autocorrelation of sensor nodes constituting the wireless sensor networks. Also, a Risk Analysis Model has developed to quickly alert the monitoring system of any fatal abnormalities when they occur. Simulation results have shown, in the case of applying the State Prediction Model, errors were smaller than otherwise. When the Risk Analysis Model is applied, the data transfer latency was reduced. The results of this study are expected to be utilized in any efficient communication method for wireless sensor network monitoring systems where all nodes are able to identify their geographic location.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.1-8
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• 2016

Current indoor intrusion detection and location tracking methods have the weakness in seamless operations in tracking the objective because the object must possess a communicating device and the limitation of the single cell size (approximate $100cm{\times}100cm$) exits. Also, the utilization of CCTV technologies show the shortcomings in tracking when the object disappear the area where the CCTV is not installed or illumination is not enough for capturing the scene (e.g. where the context-awarded system is not installed or low illumination presents). Therefore, in this paper we present an improved in-door tracking system based on sensor networks. Such system is built on a simulated scenario and enables us to detect and extend the area of surveillance as well as actively responding the emergency situation. Through simulated studies, we have demonstrated that the proposed system is capable of supplementing the shortcomings of signal cutting, and of estimating the location of the moving object. We expect the study will improve the better analysis of the intruder behavior, the more effective prevention and flexible response to various emergency situations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2641-2654
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• 2014

In the smart media environment, magazine industry has been experiencing a transition to ecosystem of value network, which includes high complexity and ambiguity. Using case study method, this article conducts research on digital convergence, the model of magazine ecosystem and adaptation strategy of global magazine companies. Research findings have it that the way of contents production of global magazines has been based on collaborative production system within communities, expert communities, creative users, media contents companies and magazine platform. The system shows different patterns and characteristics depending on magazine-driven platform, Platform-driven platform or user-driven platform. Collaboration system has been confirmed in various cases: Huffington Post and Zinio which collaborate with media contents companies, Amazon magazines and Bookish with magazine companies, Huffington Post and Wired with expert communities, and Flipboard with creative users and communities. Foreign magazine contents diverge into (paper, electronic, app and web magazine) as they start the lively trades of their contents on the magazine platform. In the area of contents uses, readers employ smart media technology effectively such as cloud computing, artificial intelligence and module individualization, making it possible for the virtuous cycle to remain in the relationship within communities, expert communities and creative users.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.626-636
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• 2009

In Mobile IP-enabled wireless LAN (WLAN), packet flows are corrupted due to the handoff of a mobile node (MN) at the link and network layers, which results in burst packet losses and can cause temporary buffer underflow in a streaming client at the MN. This transient behavior hurts time-sensitive streaming media applications severely. Among many suggestions to address this handoff problem, few studies are concerned with empirical issues regarding the practical validation of handoff options on the time-sensitive streaming media applications. In this paper, targeting seamless streaming over Mobile IP-enabled WLAN, we introduce a seamless media streaming framework that estimates accurate pre-buffering level to compensate the handoff latency. In addition, we propose a link-layer (L2) assisted seamless media streaming system as a preliminary version of this framework. The proposed system is designed to reduce the handoff latency and to overcome the playback disruption from an implementation viewpoint. A packet buffering and forwarding mechanism with L2 trigger is implemented to reduce the handoff latency and to eliminate burst packet losses generated during the handoff. A pre-buffering adjustment is also performed to compensate the handoff latency. The experimental results show that the proposed approach eliminates packet losses during the handoff and thus verify the feasibility of seamless media streaming over Mobile IP-enabled WLAN.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.138-149
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• 2006

As the environment with sensor network and ubiquitous computing is emerged, there are many demands of handling continuous, fast data such as streaming data. As work about streaming data has begun, work about management of streaming data in Publish-Subscribe system is started. The recent emergence of XML as a standard for information exchange on Internet has led to more interest in Publish - Subscribe system. A filtering technique of streaming XML data in the existing Publish- Subscribe system is using some schemes based on automata and YFilter, which is one of filtering techniques, is very popular. YFilter exploits commonality among path queries by sharing the common prefixes of the paths so that they are processed at most one and that is using the top-down approach. However, because partial matching path queries interrupt the common prefix sharing and don't calculate from root, throughput of YFilter decreases. So we use sharing of commonality among path queries with the common postfixes of the paths and use the bottom-up approach instead of the top-down approach. This filtering technique is called as PoSFilter. And we verify this technique through comparing with YFilter about throughput.