Therefore, it is hard to get the desired information from the massive data resource, which leads to the requirement of data sharing.
Since its introduction a decade ago, DDDAS has been applied to a wide range of science and technology fields, with specific focus of areas requiring fast and reliable processing of massive data streams from diverse resources.
Cisco's recent product push has also been partly focused on the cloud: Aiming at the massive data centers associated with centralized IT resources, it launched a "unified computing" product set in March, selling a combined package of servers, routers and switches.
They also have access to substantial computational resources needed to analyze massive data sets.
In today's world of massive data sets and of almost unlimited computational resources, there is a huge potential to accelerate science through increased data sharing, independent of formal collaboration or publication.
However, in most real cases, it requires many hardware resources to collect and analyze massive data.
While recent work has made great progress extracting valid and useful measurements from new data resources, few present end-to-end solutions that transform and integrate raw, massive data into estimates of travel demand and infrastructure performance.
Therefore, WSANs for CPS have to deliver massive data within hybrid traffic in a proper manner with the presence of network complexity, resource constraints, and uncertainty.
It's since been revealed that Google has gone on an unprecedented shopping spree and is in the throes of assembling what looks like the greatest artificial intelligence laboratory on Earth; a laboratory designed to feast upon a resource of a kind that the world has never seen before: truly massive data.
This involves massive data exchange.
