SeungGwan Lee

Personalized DTV program recommendation system under a cloud computing environment

A wide deployment of Internet Protocol Television (IPTV), Cable Television (CATV), Internet, User Created Contents (UCC), and Digital Television (DTV) enabled the rapid increase of channels and programs which can be selected by consumers. This was not expected when we consider the conventional television program technologies and policies. Due to these paradigm changes, hundreds of channels and programs are now available to consumers. It has become difficult and time consuming to find an interesting channel and program via the remote control or channel guide map. To refine the channel selecting processes and to satisfy the consumers requirements, we propose the Personalized DTV Program Recommendation (PDPR) system under a cloud computing environment. The proposed PDPR system analyzes and uses the viewing pattern of consumers to personalize the program recommendations, and to efficiently use computing resources.

An Accuracy Enhanced IEEE 1588 Synchronization Protocol for Dynamically Changing and Asymmetric Wireless Links

IEEE 1588 is the clock synchronization protocol for networked measurement and control system, and widely used for both wire-line and wireless network environments. IEEE 1588 was initially considered for wire-line networks, but its application is extended to wireless network especially for indoor wireless networks which can not use Global Positioning System (GPS) technology. However, the conventional IEEE 1588 assumes symmetric/asymmetric fixed data rate links, and time accuracy errors are caused for dynamically changing wireless links. We propose an enhanced synchronization algorithm for IEEE 1588 in order to compensate the offset error due to the dynamically changing data rate of the wireless link and to enhance the accuracy of time.

Network-oriented road map generation for unknown roads using visual images and GPS-based location information

Car navigation systems (CNS) have become an interesting research and industrial topic due to their wide deployment. However, updating and distribution of the road map database is a complex and high cost process. In this paper, we propose a real-time map generation and updating algorithm, which fulfills or corrects the unknown road area of the conventional road map database by using global positioning system (GPS) information and wireless communication technologies. To generate the road map of unknown roads, the proposed algorithm uses road images, which can be obtained when a driver travels unknown roads. When a driver travels unknown roads, which do not appear on the map of the car navigation system, the car navigation system extracts GPS and image information of the unknown roads. Then, the car navigation system generates the road map for the unknown roads by extracting location and road information, and updates the road map database in the car. After updating the local road map database, the car navigation system updates the master road map database, which is located at the network and is distributed to other car navigation systems. Thus, the road map database provider can update the road map database of other car navigation systems, which share the same master road map database. The proposed algorithm provides an efficient updating process of the road map database with a simplified process and reduced time for unknown road areas.

Obstacle Avoidance Path Planning for Mobile Robot Based on Multi Colony Ant Algorithm

The task of planning trajectories for a mobile robot has received considerable attention in the research literature. The problem involves computing a collision-free path between a start point and a target point in environment of known obstacles. In this paper, we study an obstacle avoidance path planning problem using multi ant colony system, in which several colonies of ants cooperate in finding good solution by exchanging good information. In the simulation, we experimentally investigate the behaviour of multi colony ant algorithm with different kinds of information among the colonies. At last we will compare the behaviour of different number of colonies with a multi start single colony ant algorithm to show the good improvement.

Modified ant colony system for coloring graphs

Ant colony system (ACS) algorithm is new meta-heuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. Recently, various methods and solutions are proposed to solve optimal solution of graph coloring problem that assign different colors for adjacency node (vi, vj). This paper introduces ANTCOL algorithm to solve solution by ant colony system algorithm that is not known well as the solution of existent graph coloring problem. After introducing the ACS algorithm and the assignment type problem, it shows the way on how to apply ACS to solve ATP. We propose ANT/spl I.bar/XRLF method which uses XRLF to solve the ANTCOL. Graph coloring result and the execution time of our method are compared with existent generating functions (ANT Random, ANT/spl I.bar/LF, ANT/spl I.bar/SL, ANT/spl I.bar/DSATUR, and ANT/spl I.bar/RLF method) Also we compare the existing generating functions with the method ANT/spl I.bar/XRLF (ANT/spl I.bar/XRLF/spl I.bar/R) where re-search is added.

Obstacle Avoidance Path Planning for Mobile Robot Based on Ant-Q Reinforcement Learning Algorithm

Path planning is an important task in mobile robot control. When the robot must move rapidly from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. In this paper, an obstacle avoidance path planning approach for mobile robots is proposed by using Ant-Q algorithm. Ant-Q is an algorithm in the family of ant colony based methods that are distributed algorithms for combinatorial optimization problems based on the metaphor of ant colonies. In the simulation, we experimentally investigate the sensitivity of the Ant-Q algorithm to its three methods of delayed reinforcement updating and we compare it with the results obtained by other heuristic approaches based on genetic algorithm or traditional ant colony system. At last, we will show very good results obtained by applying Ant-Q to bigger problem: Ant-Q find very good path at higher convergence rate.

Improved ant agents system by the dynamic parameter decision

The ant colony system (ACS) algorithm is a new meta-heuristic for hard combinational optimization problems. It is a population-based approach that uses the exploitation of positive feedback as well as a greedy search. It was first proposed for tackling the well-known traveling salesman problem (TSP). In this paper, we introduce a new version of the ACS based on a dynamic weighted updating method and a dynamic ant number decision method using a curve-fitting algorithm. An implementation to solve the TSP and performance results under various conditions are presented, and a comparison between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with the original ACS in terms of solution quality and computation speed for these problems.

Reflective middleware for location-aware application adaptation

Today mobile computing is pervasively taking over the traditional desktop computing. Mobile devices are characterized by abrupt and un-announced changes in execution context. The applications running on these devices need to be autonomous and thus dynamically adapt according to the changing context. Existing middleware support for the typical distributed applications is strictly based on component technology. Future mobile applications require highly dynamic and adaptive services from the middleware components i.e. context-aware autonomic adaptation. Traditional middleware do not address this emerging need of wide ranges of mobile applications mainly because of their monolithic and inflexible nature. It is hypothesized that such application adaptation can be achieved through meta-level protocols that can reflectively change the state and behaviors of the system. We integrate Component Technology with our active Meta Object Protocols for enabling mobile applications to become adaptive for different contexts. This paper implements the application adaptation service of this middleware. It specializes the concept of Meta Object Protocols for autonomic adaptation of mobile applications. ActiveMOP provide robust and highly flexible framework for autonomic component development for mobile applications. It proved to be a very simple and powerful way to programmatically develop location-driven applications based on autonomic components.

Ant Colony based Algorithm for Stable Marriage Problem

This paper introduces ant colony system (ACS), a distributed algorithm that is applied to the Stable Marriage Problem (SM). The stable marriage problem is an extensively-studied combinatorial problem with many practical applications. It is well known that at least one stable matching exists for every stable marriage instance. However, the classical Gale-Shapley [2] algorithm produces a marriage that greatly favors the men at the expense of the women, or vice versa. In our proposed ACS, a set of cooperating agents called ants cooperate to find stable matchings such as stable matching with man-optimal, woman-optimal, egalitarian stable matching, sex-fair stable matching. So this ACS is a novel method to solve Stable Marriage Problem. Our simulation results show the effectiveness of the proposed ACS.

FIRST: Korean Future Internet Testbed for Media-Oriented Service Overlay Network Architecture

The Future Internet Research for Sustainable Testbed (FIRST) is an experimental project in South Korea aimed at creating future internet platforms and investigating innovative ideas on developed platforms. The primary goal of the project is research and development for a media-oriented service overlay network architecture. From 2009 to 2014, dynamic media-oriented service composition technologies using virtualized network environments will be constructed, and results will be shared globally. In this paper, we explained the motivation for the FIRST project, and introduced the project itself.