Seung-Jo Bae

Design of Network Management Platform and Security Framework for WSN

Wireless sensor networks are rapidly emerging as an important area in ubiquitous computing industry. They are very tiny devices with limited energy, memory, transmission range, and computation power. So, wireless sensor networks are vulnerable to security attack such as sinkhole attack, wormhole attack, and simple power exhaustion attack. However, wireless sensor networks must be secured from obstructing the delivery of correct sensor data and from forging sensor data. The security and privacy problem related to wireless sensor networkpsilas application has become a serious issue in the real service environment. In this paper, we propose our management platform and security framework for wireless sensor networks. The proposed framework has advantages as regards secure association and intrusion detection. Furthermore, the proposed mechanism can be applied to ubiquitous application such as u-city, u-healthcare, u-defense as a secure wireless sensor network management platform.

Vector prefix and reduction computation on coarse-grained, distributed-memory parallel machines

Vector prefix and reduction are collective communication primitives in which all processors must cooperate. The authors present two parallel algorithms, the direct algorithm and the split algorithm, for vector prefix and reduction computation on coarse-grained, distributed-memory parallel machines. The algorithms are relatively architecture independent and can be used effectively in many applications such as pack/unpack, array prefix/reduction functions, and array combining scatter functions, which are defined in Fortran 90 and in High Performance Fortran. Experimental results on the CM-5 are presented.

Design of distributed memory integration framework(DMIf)

Big memory applications such as in-memory database, denovo assembly application in the human genome sequencing area, big data analytics, and large scale scientific calculation are increasing explosively. However, the big memory system has been too expensive for many researchers and students. Therefore, methods to harvest remotely distributed memory has been considered as a cost effective way to run big memory applications in the cluster environment where computing nodes are connected via high speed network. We designed and implemented a new framework, DMIf(Distributed Memory Integrated framework), which harvests idle memory of distributed nodes in a cluster and serves it to the big memory application. The collected distributed memory will provide faster data processing in a cost-effective way for the big-data/memory application.

A study on user-level remote memory extension system

The speed of memory capacity expansion of the computer system has not kept up with the speed of the increase of the memory requirement of large memory applications. Also, big memory system has been too expensive for many researchers and students. Therefore, approaches to utilize remote memory has been considered as a cost effective way to run large memory applications in the cluster environment where computing nodes are connected via high speed network. For the general users of HPC cluster system who want to run large memory application without administrators support, we suggest a user-level remote memory extension method. We designed and implemented a remote memory extension system which mapped remote memory pages to the virtual address space of the large memory application process. The system includes three components such as remote memory consumer, integrated memory manager, and memory provider. We also developed a test program and did experiment to show how good performance the user-level remote memory extension system can achieves. Through the experimental test, we will show the measured latency and bandwidth of user-level remote memory extension system for sequential access pattern and random access pattern.

A software integration architecture for support of the large-capacity memory

This article is concerned chiefly with a software integration architecture for providing a large-capacity collective memory layer on a multi-node system by using a remote direct memory access technique and a software virtualization technique. Major components described by the architecture include a memory region management module, a large-capacity collective memory service module, and a data cooperative module. As the effect of the architecture, the following merits are considered: (1) shorten access time more than a disk-based storage, (2) input /output delay prevention by prefetching mechanism, (3) increased system scalability and (4) burst real-time stream computation.

Self-provisioning and configuration system for heterogeneous diskless cluster system

As a platform for cloud services and high performance computing, cluster systems are primarily used. As the scale of the cluster system is increasing more and more and the use of heterogeneous nodes equipped with various hardware is increased, it is becoming more difficult and exhausting in time and cost to manage a cluster system in a conventional manner. In this paper, we design self-provisioning and configuration system to configure, setup, and perform provisioning for cluster system consisting of heterogeneous diskless nodes. We expect our system to make cluster system management easy and reduce time and costs to manage a cluster system.

A design of resource fault handling mechanism using dynamic resource reallocation for the resource and job management system

Due to the development of NGS technologies and the reduction of analysis cost, it is possible to perform population-scale human genome analysis. Also, large amount of genome data have been exploded recently. It is required for introduction parallel processing using High Performance Computing systems to analyse and handle these large data through genome analysis pipeline. In this paper, we propose the resource fault handling mechanism based on dynamic resource reconfiguration and delayed scheduling for data-intensive pipeline job processing such as genome analysis executed on the large cluster systems interconnected by high speed and low latency network. In order to prevent the abnormal job completion caused by lack of the specific resources, we offer the resource fault detection and handling methods. If the cause of fault is lack of resources, it can be solved by the resource re-allocation and process freezing/resuming based delayed job execution or process migration on the available node.

A workflow for parallel and distributed computing of large-scale genomic data

Workflow management systems are emerging as dominant solution in bioinformatics because they enable researchers to analyze the huge amount of data generated by modern laboratory equipment. The growth of genomic data generated by next generation sequencing (NGS) results in an increasing need to analyze data on distributed computer clusters. In this paper, we construct a semi-automated workflow system for the analysis of large-scale sequence data sets, describe a pipeline designed with parallel computation to perform the optimal computational steps required to analyze whole genome sequence data, and report the overall execution time of the pipeline using cores on multiple machines.

Workflow-based Bio Data Analysis System for HPC

Since human genome project finished, the cost for human genome analysis has decreased very rapidly. This results in the sharp increase of human genome data to be analyzed. As the need for fast analysis of very large bio data such as human genome increases, non IT researchers such as biologists should be able to execute fast and effectively many kinds of bio applications, which have a variety of characteristics, under HPC environment. To accomplish this purpose, a biologist need to define a sequence of bio applications as workflow easily because generally bio applications should be combined and executed in some order. This bio workflow should be executed in the form of distributed and parallel computing by allocating computing resources efficiently under HPC cluster system. Through this kind of job, we can expect better performance and fast response time of very large bio data analysis. This paper proposes a workflow-based data analysis system specialized for bio applications. Using this system, non-IT scientists and researchers can analyze very large bio data easily under HPC environment.

Implementation and optimization issues of the triangular patch-based terrain system

A new dynamic LOD system is recently proposed to represent fairly large artificial terrains using hierarchical triangular patches[5]. Its mesh structure is unique from other conventional methods because it is designed to reduce the total number of draw primitive calls in a frame rather than the number of primitives. Another distinctive feature is its no-triangulation during the mesh adaptation by using its hierarchical layers and pre-constructed matching blocks. The purpose of the paper is to explain its implementation issues to make the new approach more understandable. Some of optimization issues are also discussed for better implementations.