Bok-Gyu Joo

P-LEACH: An Efficient Cluster-Based Technique to Track Mobile Sinks in Wireless Sensor Networks

For a wireless sensor network (WSN) with a large number of inexpensive sensor nodes, energy efficiency is the major concern in designing network structure and related algorithms. If network collects sensor data using mobile sinks, object tracking mechanism must consider the energy efficiency of sensor nodes in the networks as a whole. Recently research works on WSNs with mobile sinks apply prediction techniques for sink tracking in order to improve tracking precision while keeping the number of active nodes to the minimum. In this paper, we analyze existing works for sink tracking in WSN and propose P-LEACH that is cluster-based prediction technique for WSN with mobile sinks. Simulation results show that P-LEACH performs better than previous techniques in terms of energy saving of sensor nodes and data transmission performance.

An Improved Social Network Analysis Method for Social Networks

Recently, Social Network Service (SNS) users are rapidly increasing, and Social Network Analysis (SNA) methods are used to analyze the structure of user relationship or messages in many fields. However, the SNA methods based on the shortest distance among nodes is time-consuming in measuring computation time. In order to solve this problem, we present a heuristic method for the shortest path search using SNS user graphs. Our proposed method consists of three steps. First, it sets a start node and a goal node in the Social Network (SN), which is represented by trees. Second, the goal node sets a temporary node starting from a skewed tree, if there is a goal node on a leaf node of the skewed tree. Finally, the betweenness and closeness centralities are computed with the heuristic shortest path search. For verification of the proposed method, we demonstrate an experimental analysis of betweenness centrality and closeness centrality, with 164,910 real data in an SNS. In the experimental results, the method shows that the computation time of betweenness centrality and closeness centrality is faster than the traditional method. This heuristic method can be used to analyze social phenomena and trends in many fields.

Community Topical “Fingerprint” Analysis Based on Social Semantic Networks

Community analysis of social networks is a widely used technique in many fields. There have been many studies on community detection where the detected communities are attached to a single topic. However, an overall topical analysis for a community is required since community members are often concerned with multiple topics. In this paper, we propose a semantic method to analyze the topical community “fingerprint” in a social network. We represent the social network data as an ontology, and integrate with two other ontologies, creating a Social Semantic Network (SSN) context. Then, we take advantage of previous topological algorithms to detect the communities and retrieve the topical “fingerprint” using SPARQL. We extract about 210,000 Twitter profiles, detect the communities, and demonstrate the topical “fingerprint”. It shows human-friendly as well as machine-readable results, which can benefit us when retrieving and analyzing communities according to their interest degrees in various domains.

Content Recommendation Method Using FOAF and SNA

With the rapid growth of user-created contents and wide use of community-based websites, content recommendation systems have attracted the attention of users. However, most recommendation systems have limitations in properly reflecting each user’s characteristics, and difficulty in recommending appropriate contents to users. Therefore, we propose a content recommendation method using Friend-Of-A-Friend (FOAF) and Social Network Analysis (SNA). First, we extract user tags and characteristics using FOAF, and generate graphs with the collected data, with the method. Next, we extract common characteristics from the contents, and hot tags using SNA, and recommend the appropriate contents for users. For verification of the method, we analyzed an experimental social network with the method. From the experiments, we verified that the more users that are added into the social network, the higher the quality of recommendation increases, with comparison to an item-based method. Additionally, we can provide users with more relevant recommendation of contents.

An Improved Method for Measurement of Gross National Happiness Using Social Network Services

Studies on the measurement of happiness have been utilized in a variety of areas; in particular, it has played an important role in the measurement of society stability. As the number of users of Social Network Services (SNSs) increase, efforts are being made to measure human well-being by analyzing user messages in SNSs. Most previous works mainly counted positive and negative words; they did not consider the grammar and emotion. In this paper, we reorganize the mechanism to harness the advantages of (a) Part-Of-Speech (POS) tagging for grammatical analysis, and (b) the SentiWordNet lexicon for the assignment of sentiment scores for emotion degree. We suggest a modified formula for calculating the Gross National Happiness (GNH). To verify the method, we gather a real-world dataset from 405,700 Twitter users, measure the GNH, and compare it with the Gallup well-being release. We demonstrate that the method has more precise computation ability for GNH.

QoS-Based Path Switching Mechanism in Mobile SCTP

In mobile SCTP, a mobile terminal has two or more network interfaces and vertical handover occurs when it moves from one network to another. The delay due to the handover process and the slow-start phase of SCTPs congestion control after handover cause substantial performance degradation. If the mobile node goes back and forth frequently, excessive handovers occur and data transmission quality deteriorates. In order to provide the required level of QoS for on-going application, the frequency of handovers should be kept minimized. In this paper, we propose a transport layer handover mechanism using the mobile SCTP. We take the QoS requirements of application as the major criterion in deciding path switching. In our mechanism, the mobile node in overlapping area does not perform handover if the current network metrics satisfy the QoS requirements of on-going application. Both analytic evaluation and simulation results show that the proposed mechanism significantly improves the throughput by suppressing unnecessary handovers. Our research results can also be applied to distributed mobile sensor networks.

A self-configuration mechanism for high-availability clusters

Most high-availability (HA) solutions currently used are based on the pre-configuration done by human administrators. If the configuration between machines participating in the HA cluster can be automated, services clustered can be provided more efficiently. For realizing this concept, the server agent and service description server (SDS) are designed and implemented in this paper. The server agent exchanges several messages with other servers and SDS. SDS is the central server that manages information needed for each machine to do “self-configuration”. We also implement a web-based monitoring tool to watch the status of the overall system.

Route Optimization Technique to Support Multicast in Mobile Networks

The technology called Network Mobility (NEMO) is proposed recently by IETF to support the network mobility. Meanwhile, as the needs of group communications increase in the internet, supporting multicast services became a challenging issue on NEMO as on Mobile IP. This paper explores issues and problems of providing multicast service on mobile networks and presents a route optimization technique along with an architecture that enables optimal and efficient multicast service on NEMO environments.

Dual transmission architecture for mobile multicasting

With the popularity of mobile devices, Internet service providers are interested in supporting mobile applications. Mobile IP standards have been developed without considering multicast services. This paper explores the issues of multicasting for mobile hosts and problems of previous approaches, and proposes dual-transmission architecture for mobile multicasting (DTAMM), which provides reliable and optimal multicast communication in mobile environments. Proposed architecture is based on the standard protocols and, with some functional extensions to network components, solves most of the problems currently identified. We also developed a simple cost-analytic model to evaluate its performance.

An Intelligent Dynamic Context-Aware System Using Fuzzy Semantic Language

The prevalence of smart devices and the wireless Internet environment have enabled users to exploit environmental sensor data in a variety of fields. This has engendered various research issues in the development of context-awareness technology. In this paper, we propose a novel method where semantic web technology and the fuzzy concept are used to perform tasks that express and infer the user’s dynamic context, in distributed heterogeneous computing environments. The proposed method expresses environmental information using numerical values, and converts them into fuzzy OWL. Then, we make inferences based on the user context, using FiRE, a fuzzy inference engine. The suggested method allows us to describe user context information in heterogeneous environments. Because we use fuzzy concepts to represent contextual information, we can easily express its degree or status.