Euihyun Jung

Mobile agent network for supporting personal mobility

Needs and interests of the personal mobility have been increasing, because of the rapid development of wireless communication technologies and computer networks. Telecommunication sectors have made a lot of efforts to provide the personal mobility resulting in the development of PCN (Personal Communication Networks) or UPT (Universal Personal Telecommunications) services. However, the mobility service in the Internet has been mainly focused on the host mobility such as Mobile IF, while the personal mobility has been neglected relatively. In this paper, the agent network, the virtual network mapped onto physical networks, is proposed to support the personal mobility on the Internet. Mobile agent technology is adopted to build the agent network. The agent engine is designed and implemented with Java, and the Agent/Servant architecture is suggested to complement restrictions of Java applets.

Composite methods for improving Spray and Wait routing protocol in Delay Tolerant Networks

Delay Tolerant Networks have been emerged to support intermittent connectivity of frequently partitioned networks. A routing issue of Delay Tolerant Networks is concerned about the extremely long delay of opportunistic intermittent connections. For considering routing protocols of Delay Tolerant Networks, a forwarding decision and the buffer management scheme are important to improve the successful message delivery opportunity. In this paper, we propose the composite methods to improve Spray and Wait routing protocol. The proposed method consists of the use of an ACK message and message forwarding based on the delivery probability. The proposed composite methods can resolve the disadvantages of Spray and Wait routing protocol. In according to the simulation, the proposed method shows better delivery rate and lower communication overhead compared to other routing protocols.

iotSilo: The Agent Service Platform Supporting Dynamic Behavior Assembly for Resolving the Heterogeneity of IoT

Although a lot of researchers have painted a rosy picture of Internet of Things (IoT), there have been no widely accepted solution and related standards until now. To achieve the successful realization of IoT, the close collaboration of devices is the primary requisite. However, the heterogeneity of devices such as different hardware or network connectivity prohibits the realization of IoT. In order to overcome the heterogeneity issue, we suggested the agent service platform named iotSilo in which agents can communicate and cooperate on behalf of their devices. With this delegation approach, the iotSilo can support diverse devices without worrying about their differences. In designing an agent, several software design patterns are adopted to enable the agent to assemble behaviors for hiding the heterogeneity of devices. To investigate the effectiveness of the iotSilo, we developed eleven different types of the IoT devices to emulate real world things with Arduino, deployed the devices in both Korea and Japan, and then conducted three experiments.

A radio-aware routing algorithm for reliable directed diffusion in lossy wireless sensor networks.

In Wireless Sensor Networks (WSNs), transmission errors occur frequently due to node failure, battery discharge, contention or interference by objects. Although Directed Diffusion has been considered as a prominent data-centric routing algorithm, it has some weaknesses due to unexpected network errors. In order to address these problems, we proposed a radio-aware routing algorithm to improve the reliability of Directed Diffusion in lossy WSNs. The proposed algorithm is aware of the network status based on the radio information from MAC and PHY layers using a cross-layer design. The cross-layer design can be used to get detailed information about current status of wireless network such as a link quality or transmission errors of communication links. The radio information indicating variant network conditions and link quality was used to determine an alternative route that provides reliable data transmission under lossy WSNs. According to the simulation result, the radio-aware reliable routing algorithm showed better performance in both grid and random topologies with various error rates. The proposed solution suggested the possibility of providing a reliable transmission method for QoS requests in lossy WSNs based on the radio-awareness. The energy and mobility issues will be addressed in the future work.

A robust digital watermarking adopting 2d barcode

In this paper, a new watermarking algorithm using 2D barcode is proposed. The 2D barcode means 2-dimensional barcode that contains more information than conventional 1-dimensional barcodes. For error correction, 2D barcode allow the recognition of barcodes that are up 60% damaged. Therefore, the 2D barcode as watermark can be survived when it used in highly noisy environment. In this paper, a new wavelet based watermarking algorithm using 2D barcode as watermark is proposed. Dynamically generated 2D barcode is inserted as watermark in wavelet domain. From the experimental result, the proposed algorithm shows better invisibility and robustness comparing with the conventional methods using plain image as watermark.

UniRSS: a new RSS framework supporting dynamic plug-in of RSS extension modules

Due to the proliferation of information exchange via Internet, users suffer from information overload For this reason, RSS is now widely adopted to deliver latest information to users without human intervention It is also used to deliver customized data using extension modules However an inter-operability issue among RSS applications using different extension modules has been raised because the processing of extension module has to be performed in the source code level of RSS applications To resolve this interoperability issue, we propose a new RSS framework, UniRSS, which can support extension modules via a unified interface UniRSS suggests an architecture composed of a pair of describing schema and a delegation code model to support any kind of extension modules in the code level It supports both RSS 1.0 and RSS 2.0, and it also provides intelligent syndication using reasoning code insertion for RSS 1.0.

An Agent Modeling for Overcoming the Heterogeneity in the IoT with Design Patterns

The Internet of Things (IoT) has been considered as a core infrastructure that provides the connectivity to anyone, anywhere, anytime and especially anything. Due to this advantage, the IoT is expected to change the whole society and to enrich people’s everyday life, but there are a lot of technical issues in realizing the IoT. Among them, the heterogeneity is an urgent and essential issue that cannot be easily resolved. In this paper, we described an agent modeling that can hide the heterogeneity of devices using the Strategy, Dependency Injection, and Reflection design patterns. The designed agent was implemented as the agent system named iSilo and various devices were developed and bound to the agents in the iSilo. Several experiments were conducted in Korea and Japan and these evaluations showed the proposed modeling could be a novel solution to overcome the heterogeneity in the IoT.

A smart sensor overlay network for ubiquitous computing

Sensor networks have been considered as a base technology for constructing ubiquitous computing environment. However, most researches about sensor networks have not focused on ubiquitous computing but mainly focused on efficiency of sensor networks itself. Ubiquitous computing requires sensor networks to be accessed in a transparent and abstract manner from the outer world. However the requirements cannot be easily achieved because of physical restrictions of sensor networks and centralized data processing scheme. In this paper, we have designed a sensor overlay network that enables ubiquitous computing applications to consider sensor networks as an ordinary component of ubiquitous computing environment. Virtual sensors and actuators on the overlay network cooperate with each other and provide intelligent decision that was impossible to be implemented with current physical sensor networks. The proposed overlay network also provides dynamic service composition and device integration essential to ubiquitous computing. To evaluate the usefulness of the designed system, the overlay network is implemented and simulated on J-Sim simulator.

A Bayesian Network Approach for Discovering Variables Affecting Youth Depression

Bayesian Networks have been used for data mining in many domains, but they have been rarely adopted in educational domain. In this paper, we model a Bayesian Network to discover which variables are in charge of youth depression and how strong the variables influence. For this study, Korean Children and Youth Panel Survey data are used and Markov Blanket is adopted to learn the Bayesian Network and to choose the relevant variables. In the results, “life satisfaction”, “social withdrawal”, “mobile phone dependency”, “attention”, “caregiver abuse”, and “aggressiveness” are extracted as the relevant variables to youth depression, therefore caregivers should pay attention to these variables of youths to reduce their depression. This paper shows Bayesian Networks are quite effective in finding the causal variables and their effects in educational domain.

A Data-Driven Decision Making with Big Data Analysis on DNS Log

Domain Name System (DNS) log has been considered as a great source of valuable information for the decision making on government policy or business strategy because querying DNS is the first step of all Internet activities. Due to the size of DNS log, Hadoop is considered as a prominent solution, but the geographical dispersal of DNS log hinders to adopt it in an ordinary way. Hadoop assumes all data source should be located on a single Hadoop File System (HDFS), but DNS log is stored on DNS servers dispersed all over the world. To resolve this issue, a new method named “Localized Analysis & Merge (LAM)” is proposed in this paper. The proposed method enables Hadoop to analyze DNS log on the dispersed DNS servers and it reduced the whole processing time dramatically. Also, the LAM method showed that DNS log can be used to extract a lot of valuable information such as a malware detection, the access frequency over countries, etc.