Hyun-Hwa Choi

• Electronics and Telecommunications Research Institute

In the past few years, cloud computing has been realized and has achieved advancement. Sincemany cloud systems and providers have been deployed in this world, various models and platforms have been developed to support multiple cloud (i.e., multi-cloud) environments (e.g., inter-cloud, federated cloud, distributed cloud, hybrid cloud, multi-cloud m...

Today's data intensive applications require to process large amount of data on cluster systems that consist of commodity computing nodes with high performance network interconnects. Individual computing nodes in the cluster system have indentical resource specification although applications vary greatly in their resource needs. From imbalance of th...

Disclosed herein are an apparatus and method for managing a data stream distributed parallel processing service. The apparatus includes a service management unit, a Quality of Service (QoS) monitoring unit, and a scheduling unit. The service management unit registers a plurality of tasks constituting the data stream distributed parallel processing...

Application’s memory footprints are growing exponentially due to an increase in their data set and additional software layer. Modern RDMA capable networks such as InfiniBand and Myrinet with low latency and high bandwidth provide us a new vision to utilize remote memory. Remote idle memory can be exploited to improvement performance of memory inten...

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...

Although conventional index structures provide various nearest-neighbor search algorithms for high-dimensional data, there are additional requirements to increase search performances, as well as to support index scalability for large-scale datasets. To support these requirements, we propose a distributed high-dimensional index structure based on cl...

We are currently witnessing a rapid growth of image data, triggered by the popularity of the Internet and the huge amount of user-generated content from Web 2.0 applications. To address the demanding search needs caused by large-scale image collections, two major approaches for high-dimensional data in cluster systems have been proposed: Speeding u...

Most of the distributed high-dimensional indexing structures provide a reasonable search performance especially when the dataset is uniformly distributed. However, in case when the dataset is clustered or skewed, the search performances gradually degrade as compared with the uniformly distributed dataset. We propose a method of improving the k-near...

Recently, the proliferation of the web and digital photography has resulted in the need of a distributed storage system for managing large scale data and an indexing technique for supporting efficient nearest neighbor search on high-dimensional data. One of the most challenging areas in the fields of a distributed data managing and image processing...