Challenges and opportunities for analysis based research in big data Conference Paper

abstract

• One response to the proliferation of massive datasets in many fields has been to develop ingenious ways to throw resources at the problem, for example, using massive fault tolerant storage architectures, supercomputing platforms, and parallel graph computation models. However, not all environments can support this scale of resources, and not all queries need an exact response. Massive and diverse operational datasets have been employed by large Internet Service Providers for a number of years, and mathematical methods have underpinned their response to the challenges of data scale, incompleteness and complexity that are prevalent both in ISP data and in big data more generally. This talk reviews some recent progress in this direction, and surveys some new roles for sampling methods in Big Data.

name of conference

• 2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)

authors

• Duffield, Nick

published proceedings

• 2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC)

author list (cited authors)

• Duffield, N., & Wu, J.

citation count

• 0

complete list of authors

• Duffield, Nick||Wu, Jie

publication date

• December 2014

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Performance, Computing and Communications Conference, Proceedings  Journal

keywords

• 46 Information And Computing Sciences
• 4605 Data Management And Data Science
• 4606 Distributed Computing And Systems Software
• Generic Health Relevance
• Networking And Information Technology R&d (nitrd)

Digital Object Identifier (DOI)

• 10.1109/pccc.2014.7017014

start page

• 1

end page

• 1

URL

• http://dx.doi.org/10.1109/pccc.2014.7017014