Myoungjin Kim

SMCC: Social Media Cloud Computing Model for Developing SNS Based on Social Media

Social media-based Social Networking Service (SNS) has grown dramatically over the last decade. Numerous users have strengthened their human networks by joining SNS. Although many service providers tend to develop SNS according to the needs of users, it is difficult to develop SNS based on large amounts of social media using traditional techniques with related to processing and transmitting it in large and DB system for storing it. Therefore, in this paper, we present a new concept of Social Media Cloud Computing model (SMCC) combined with cloud computing environment that provides elastic computing resources for processing and storing big social media data and platforms for providing SNS’s development environments. Our services deal with the whole cloud computing services such as SaaS, PaaS and IaaS.

CloudDMSS: robust Hadoop-based multimedia streaming service architecture for a cloud computing environment

The delivery of scalable, rich multimedia applications and services on the Internet requires sophisticated technologies for transcoding, distributing, and streaming content. Cloud computing provides an infrastructure for such technologies, but specific challenges still remain in the areas of task management, load balancing, and fault tolerance. To address these issues, we propose a cloud-based distributed multimedia streaming service (CloudDMSS), which is designed to run on all major cloud computing services. CloudDMSS is highly adapted to the structure and policies of Hadoop, thus it has additional capacities for transcoding, task distribution, load balancing, and content replication and distribution. To satisfy the design requirements of our service architecture, we propose four important algorithms: content replication, system recovery for Hadoop distributed multimedia streaming, management for cloud multimedia management, and streaming resource-based connection (SRC) for streaming job distribution. To evaluate the proposed system, we conducted several different performance tests on a local testbed: transcoding, streaming job distribution using SRC, streaming service deployment and robustness to data node and task failures. In addition, we performed three different tests in an actual cloud computing environment, Cloudit 2.0: transcoding, streaming job distribution using SRC, and streaming service deployment.

A Hadoop-based Multimedia Transcoding System for Processing Social Media in the PaaS Platform of SMCCSE

In this paper, we use a quadrotor-based mobile sink to gather sensor data from the terrestrial deployed wireless sensor network. By analyzing the flight features of the mobile sink node, we theoretically study the flight constraints of height, velocity, and trajectory of the mobile sink node so as to communicate with the terrestrial wireless sensor network. Moreover, we analyze the data amount which the mobile sink can send when it satisfies these flight constraints. Based on these analysis results, we propose a data acquisition approach for the mobile sink node, which is discussed detailed in terms of network performance such as the transmission delay, packet loss rate, sojourning time and mobile trajectory when given the flying speed and height of the mobile sink node. Extensive simulation results validate the efficiency of the proposed scheme.

Design and Implementation of UPnP-Based Surveillance Camera System for Home Security

With the rapid development of mobile devices and Internet services, managing home security with these devices and services is gaining popularity. To expand the range of usability of conventional home surveillance cameras, we propose the UPnP-based Surveillance Camera System (USCS), which employs UPnP technology to search, control, and manage IP-based cameras. With UPnP, interconnected equipment and the control network inside the home can be accessed for data sharing, communication, and entertainment. However, the current UPnP was originally designed for local networks. Therefore, we integrated the UPnP control module into the Open Service Gateway Initiative (OSGi) framework to access UPnP services from a remote network. The control point is an external network that can access the UPnP device, which is hosted in a home area network via USCS. Our system showed improved searching, management, discovery, and manipulation of IP-based cameras in a home network using our system, compared to a conventional system. Users can use a mobile device to monitor the home security status in real time by a remote access function provided by OSGi. Hence, users can monitor their homes more efficiently and instantly, ensuring the safety of house members and the property.

Implementation of MapReduce-based image conversion module in cloud computing environment

In recent years, the rapid advancement of the Internet and the growing number of people using social networking services (SNSs) have facilitated the sharing of multimedia data. However, multimedia data processing techniques such as transcoding and transmoding impose a considerable burden on the computing infrastructure as the amount of data increases. Therefore, we propose a MapReduce-based image-conversion module in cloud computing environment in order to reduce the burden of computing power. The proposed module consists of two parts: a storage system, i.e., Hadoop distributed file system (HDFS) for image data and a MapReduce program with a Java Advanced Imaging (JAI) library for image transcoding. It can process image data in distributed and parallel cloud computing environments, thereby minimizing the computing infrastructure overhead. In this paper, we describe the implementation of the proposed module using Hadoop and JAI. In addition, we evaluate the proposed module in terms of processing time under varying experimental conditions.

A Robust Cloud-Based Service Architecture for Multimedia Streaming Using Hadoop

Delivering scalable rich multimedia applications and services on the Internet requires sophisticated technologies for transcoding, distributing, and streaming content. Although cloud computing provides an infrastructure for such technologies, the specific challenges of task management, load balancing, and fault tolerance remain. To address these issues, we propose a cloud-based distributed multimedia streaming service, or CloudDMSS. The system is designed to run on all major cloud computing services, and is highly adapted to the structure and policies of Hadoop, which give it additional capabilities for transcoding, task distribution, load balancing, content replication and distribution.

Performance Evaluation of Image Conversion Module Based on MapReduce for Transcoding and Transmoding in SMCCSE

We presented the authors SMCCSE (Social Media Cloud Computing Service Environment) that supports the development and construction of Social Networking Service (SNS) based on large amounts of social media including audio, video and image in earlier publication. The main contributions of this paper are to present how to design and implement Map Reduce-based image conversion module for social media transcoding and transmoding that are the core functions in our SMCCSE as well as to verify performance evaluation results for image conversion module. In this paper, we show a partially functional image conversion module based on Hadoop in SMCCSE except for video and audio. Moreover, we discuss experimental results performed on a 28 node SMCCSE cluster under varying experimental conditions in order to verify the performance for image conversion function.

An Intelligent Multi-Agent Model for Resource Virtualization: Supporting Social Media Service in Cloud Computing

With the rapid growth Internet, communication technologies and hand devices, there are a lot of communication and social activities of users in various information services based on SNS. As the availability of social media contents generated from users increases dramatically, the task of providing high-quality media contents in social media sites that need user contributions is emerging as unimportant issue in IT field. In this paper, we propose an intelligent multi-agent model for resource virtualization (IMAV) to automatically allocate service resources suitable for mobile devices in cloud computing environment supporting social media services. Our model can recommend optimized resource allocation suitable for mobile devices through virtualization rules and multi-agent. IMAV consists of user agent, distributed agent, gathering agent, virtualization register agent manager and system resource manager.

A Model of Multi-agent Design for Virtualization Resource Configuration in Cloud Computing

In recent years, social network service based on mobile devices has obtained lots of interests from many users, developers as well as service providers. However, many users do not gain high quality social media services due to the fact that mobile devices have bad performance of hardware. In order to overcome the limitation of hand devices, most providers are applying cloud computing techniques, especially virtualization to SNS. In this paper, we propose multi-agent model for virtualization resource configuration that automatically allocates service resources suitable for mobile devices in cloud computing environment. The proposed model infers user on-demand by analyzing and learning user context information. In addition, multi-agent model allocates service resources depending on types of usage so that users can utilize reliable service resources.

A TMO Based Real-Time Model: Supporting u-GIS Informative Construction Technology Innovation

In the real world it is very difficult to implement real-time models in uncontrolled distributed environments and to support well-defined interfaces from real-time systems to external systems. An ongoing project for ubiquitous computing environments, u-GIS based informative construction technology innovation project needs a system to handle and control various data (sensor data, visual data, equipment status data, etc.) generated from remotely distributed construction sites in real time. The main purpose of this paper is to study how to support real-time applications, to design TMO-based distributed real-time processing techniques for real industrial applications, and to develop a TMO-based real-time model with less strict real-time constraints in ubiquitous environments. We propose an easy-to-use TMO-based real-time model with less strict real-time constraints for u-GIS based informative construction technology innovation project.