TY - GEN
T1 - NEST
T2 - 17th International IFIP TC6 Networking Conference, Networking 2018
AU - Khalil, Karim
AU - Aqil, Azeem
AU - Krishnamurthy, Srikanth V.
AU - Abdelzaher, Tarek
AU - Kaplan, Lance
N1 - Funding Information:
Acknowledgment: This work was partially supported by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. This work was also partially supported by the NSF CPS grant 1544969.
Publisher Copyright:
© 2018 IFIP
PY - 2018
Y1 - 2018
N2 - In many emerging data retrieval applications, in response to queries, consumers are interested in getting a summarized version of content quickly rather than retrieving all available data. Recently, Named Data Networks (NDN) have been considered for efficient transfer of summarized information, but the research is still in its infancy. In this paper, we propose NEST, a novel transport protocol for delivering extractive summaries of a dataset distributed across multiple producers over NDN. The goal is to exploit diversity in network conditions between a consumer and different producers towards delivering the consumer-specified summary while minimizing latency. NEST first creates a unified hierarchical representation of the available distributed content using state-of-the-art distributed clustering. Then, using this representation of the dataset, the protocol creates interest messages based on which consumers can opportunistically retrieve representative data objects from the best producers while adapting to dynamic network conditions by capitalizing on the flexibility offered by the NDN infrastructure. We implement NEST on the Mini-NDN network emulator and evaluate its performance using datasets collected from Twitter. Our experimental results show that NEST takes advantage of producer diversity achieving large latency reduction gains of up to 50% compared to baseline protocols.
AB - In many emerging data retrieval applications, in response to queries, consumers are interested in getting a summarized version of content quickly rather than retrieving all available data. Recently, Named Data Networks (NDN) have been considered for efficient transfer of summarized information, but the research is still in its infancy. In this paper, we propose NEST, a novel transport protocol for delivering extractive summaries of a dataset distributed across multiple producers over NDN. The goal is to exploit diversity in network conditions between a consumer and different producers towards delivering the consumer-specified summary while minimizing latency. NEST first creates a unified hierarchical representation of the available distributed content using state-of-the-art distributed clustering. Then, using this representation of the dataset, the protocol creates interest messages based on which consumers can opportunistically retrieve representative data objects from the best producers while adapting to dynamic network conditions by capitalizing on the flexibility offered by the NDN infrastructure. We implement NEST on the Mini-NDN network emulator and evaluate its performance using datasets collected from Twitter. Our experimental results show that NEST takes advantage of producer diversity achieving large latency reduction gains of up to 50% compared to baseline protocols.
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M3 - Conference contribution
AN - SCOPUS:85127935550
T3 - 17th International IFIP TC6 Networking Conference, Networking 2018
SP - 280
EP - 288
BT - 17th International IFIP TC6 Networking Conference, Networking 2018
PB - IFIP
Y2 - 14 May 2018 through 16 May 2018
ER -