NDLI: RTIC-C: A Big Data System for Massive Traffic Information Mining

Content Provider	IEEE Xplore Digital Library
Author	Jianjun Yu Fuchun Jiang Tongyu Zhu
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China (Tongyu Zhu) \|\| Comput. Network Inf. Center, Beijing, China (Jianjun Yu; Fuchun Jiang)
Abstract	Traffic information system may produce massive and complex traffic data with the process of collecting real-time original GPS (Global Positioning System) data, matching positions to a map and generating traffic flow information, which brings great markets for even-worse traffic condition in China. Howerver, several issues would occur when we reuse these massive traffic data for history data mining applying on-hand database management tools or traditional data processing apporaches, such as massive storage, high performance processing, open interface. "Big Data" system usually includes data sets with sizes beyond the ability of commonly-used software tools to capture, manage, and process the data within a tolerable elapsed time. With this difficulty and the advantage of "Big Data", we schemed RTIC-C system to handle sensemaking over large quantities of traffic data based on cloud computing technique. RTIC-C designs a distributed data management service to support large scale of data storage, a parallel distributed computing framework for diverse kinds of mining applications based on Map-Reduce mechanism, a restful Web services interface to support third-party mining applications. Experiments on a massive traffic data sets showed that RTIC-C achieves considerable performance comparing with traditional traffic data mining applications.
Sponsorship	IEEE Comput. Soc.
Starting Page	395
Ending Page	402
File Size	469694
Page Count	8
File Format	PDF
e-ISBN	9781479928309
DOI	10.1109/CLOUDCOM-ASIA.2013.91
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cloud computing Cloud Computing Distributed databases Software as a Service (SaaS) Computer architecture Real-time Traffic Information Big Data Real-time systems Data mining Accidents
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

RTIC-C: A Cloud Computing Platform for History Data Mining of Traffic Information

e-MinZu: A Software Service Architecture Based on Saas for Massive Data Source

A Novel and Flexible Cloud Architecture for Data-Centric Applications

A Software Chain Approach to Big Data Stream Processing and Analytics

SMASH: A Cloud-Based Architecture for Big Data Processing and Visualization of Traffic Data

Towards Real-Time Analytics in the Cloud

Tenant Level Checkpointing of Meta-data for Multi-tenancy SaaS

Data model for Big Data in cloud environment

Formal representation of service interactions for SaaS based applications

RTIC-C: A Big Data System for Massive Traffic Information Mining

Similar Documents

RTIC-C: A Cloud Computing Platform for History Data Mining of Traffic Information

e-MinZu: A Software Service Architecture Based on Saas for Massive Data Source

A Novel and Flexible Cloud Architecture for Data-Centric Applications

A Software Chain Approach to Big Data Stream Processing and Analytics

SMASH: A Cloud-Based Architecture for Big Data Processing and Visualization of Traffic Data

Towards Real-Time Analytics in the Cloud

Tenant Level Checkpointing of Meta-data for Multi-tenancy SaaS

Data model for Big Data in cloud environment

Formal representation of service interactions for SaaS based applications

RTIC-C: A Big Data System for Massive Traffic Information Mining