Publications by Ho Young Jeung

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As the Sensor Internet starts to become reality, increasingly heterogeneous sensor networks are becoming interconnected into federated sensor networks and provide huge volumes of sensor data for a variety of applications to large user communities, such as ...

Sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this dat ...

Minimizing communication cost is a fundamental problem in large-scale federated sensor networks. Maintaining model-based views of data streams has been highlighted because it permits efficient data communication by transmitting parameter values of models, ...

As mobile cloud computing facilitates a wide spectrum of smart applications, the need for fusing various types of data available in the cloud grows rapidly. In particular, social and sensor data lie at the core in such applications, but typically processed ...

In automotive applications, movement-path prediction enables the delivery of predictive and relevant services to drivers, e.g., reporting traffic conditions and gas stations along the route ahead. Path prediction also enables better results of predictive r ...

Although efficient processing of probabilistic databases is a well-established field, a wide range of applications are still unable to benefit from these techniques due to the lack of means for creating probabilistic databases. In fact, it is a challenging ...

Modern positioning technologies enable collecting trajectories from moving objects across different locations over time, typically containing time-varying measurement errors of positioning systems. Unfortunately, current models on uncertain trajectories ar ...

This document introduces the TimeCloud Front End, a web-based interface for the TimeCloud platform that manages large-scale time series in the cloud. While the Back End is built upon scalable, fault-tolerant distributed systems as Hadoop and HBase and take ...

As the volumes of sensor data being accumulated are likely to soar, data compression has become essential in a wide range of sensor-data applications. This has led to a plethora of data compression techniques for sensor data, in particular model-based appr ...

As sensors continue to proliferate, the capabilities of effectively querying not only sensor data but also its metadata becomes important in a wide range of applications. This paper demonstrates a search system that utilizes various techniques and tools fo ...

Sensor network deployments are a primary source of massive amounts of data about the real world that surrounds us, measuring a wide range of physical properties in real time. However, in large-scale deployments it becomes hard to eectively exploit the data ...

This paper presents a new approach to measuring similarity over massive time-series data. Our approach is built on two principles: one is to parallelize the large amount computation using a scalable cloud serving system, called TimeCloud. The another is to ...

Ho Young Jeung

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Effective Metadata Management in Federated Sensor Networks

Enabling Query Technologies for the Semantic Sensor Web

Efficiently Maintaining Distributed Model-Based Views on Real-Time Data Streams

Cloud based Social and Sensor Data Fusion

Path Prediction and Predictive Range Querying in Spatial Network Databases

Creating Probabilistic Databases from Imprecise Time-Series Data

Managing Evolving Uncertainty in Trajectory Databases

Building a Front End for a Sensor Data Cloud

An Evaluation of Model-Based Approaches to Sensor Data Compression

Advanced Search, Visualization and Tagging of Sensor Metadata

Semantic Sensor Data Search in a Large-Scale Federated Sensor Network

Deriving Semantic Sensor Metadata from Raw Measurements

Model-Based Similarity Measure in TimeCloud