Needle in a haystack: Cost-Effective data analytics for real-time cloud sharing

Real-time file sharing is important to improve the quality of cloud services. Current cloud systems however fail to efficiently offer cost-effective data analytics due to slow response and energy inefficiency. In order to support real-time processing and improve energy efficiency in the cloud, this paper proposes a novel cost-effective data analytics scheme, called Needle. The idea behind Needle is to use flat-addressing and content-aware naming approaches to deliver high performance of network transmission. Needle leverages a suitable division-of-labor model between core and edge network nodes to efficiently support content-aware queries in the cloud data center networks. Experimental results demonstrate that Needle is able to support cloud sharing service in a real-time and efficient manner.