sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
FacebookTwitterGoogle PlusLinkedInYouTubeFlickr

SCHEDULE: NOV 16-21, 2014

When viewing the Technical Program schedule, on the far righthand side is a column labeled "PLANNER." Use this planner to build your own schedule. Once you select an event and want to add it to your personal schedule, just click on the calendar icon of your choice (outlook calendar, ical calendar or google calendar) and that event will be stored there. As you select events in this manner, you will have your own schedule to guide you through the week.

FAST: Near Real-time Searchable Data Analytics for the Cloud

SESSION: Machine Learning and Data Analytics

EVENT TYPE: Papers

TIME: 11:30AM - 12:00PM

SESSION CHAIR: Hank Childs

AUTHOR(S):Yu Hua, Hong Jiang, Dan Feng

ROOM:388-89-90

ABSTRACT:

With the explosive growth in data volume and complexity and the increasing need for highly efficient searchable data analytics, existing cloud storage systems have largely failed to offer an adequate capability for real-time data analytics. To address this problem, we propose a near-real-time and cost-effective searchable data analytics methodology, called FAST. The idea behind FAST is to explore and exploit the semantic correlation within and among datasets via correlation-aware hashing and manageable flat-structured addressing to significantly reduce the processing latency, while incurring acceptably small loss of data-search accuracy. FAST supports several types of data analytics, which can be implemented in existing searchable storage systems. We conduct a real-world use case in which children reported missing in an extremely crowded environment are identified in a timely fashion by analyzing 60 million images using FAST. Extensive experimental results demonstrate the efficiency and efficacy of FAST in the performance improvements and energy savings.

Chair/Author Details:

Hank Childs (Chair) - University of Oregon and Lawrence Berkeley National Laboratory

Yu Hua - Huazhong University of Science & Technology

Hong Jiang - University of Nebraska-Lincoln

Dan Feng - Huazhong University of Science & Technology

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar


Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society