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

Yu Hua, Dan Feng
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="" style="color: black;">2014 IEEE 22nd International Symposium of Quality of Service (IWQoS)</a> </i> &nbsp;
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
more &raquo; ... 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/iwqos.2014.6914316</a> <a target="_blank" rel="external noopener" href="">dblp:conf/iwqos/HuaF14</a> <a target="_blank" rel="external noopener" href="">fatcat:wtn3joxa6rag5gpln6fs4fmmgi</a> </span>
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