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Distributed network querying with bounded approximate caching

Publication ,  Journal Article
Chandramouli, B; Yang, J; Vahdat, A
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
July 7, 2006

As networks continue to grow in size and complexity, distributed network monitoring and resource querying are becoming increasingly difficult. Our aim is to design, build, and evaluate a scalable infrastructure for answering queries over distributed measurements, at reduced costs (in terms of both network traffic and query latency) while maintaining required precision. In this infrastructure, each network node owns a set of numerical measurements and actively maintains bounds on these values cached at other nodes. We can answer queries approximately, using bounds from nearby caches to avoid contacting the owners directly. We focus on developing efficient and scalable techniques to place, locate, and manage bounded approximate caches across a large network. We have developed two approaches: One uses a recursive partitioning of the network space to place caches in a static, controlled manner, while the other uses a locality-aware distributed hash table to place caches in a dynamic and decentralized manner. In this paper, we focus on the latter approach. Experiments over a large-scale emulated network show that our techniques are very effective in reducing query costs while generating an acceptable amount of background traffic; they are also able to exploit various forms of locality that are naturally present in queries, and adapt to volatility of measurements. © Springer-Verlag Berlin Heidelberg 2006.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

July 7, 2006

Volume

3882 LNCS

Start / End Page

374 / 388

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Chandramouli, B., Yang, J., & Vahdat, A. (2006). Distributed network querying with bounded approximate caching. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3882 LNCS, 374–388. https://doi.org/10.1007/11733836_27
Chandramouli, B., J. Yang, and A. Vahdat. “Distributed network querying with bounded approximate caching.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3882 LNCS (July 7, 2006): 374–88. https://doi.org/10.1007/11733836_27.
Chandramouli B, Yang J, Vahdat A. Distributed network querying with bounded approximate caching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2006 Jul 7;3882 LNCS:374–88.
Chandramouli, B., et al. “Distributed network querying with bounded approximate caching.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3882 LNCS, July 2006, pp. 374–88. Scopus, doi:10.1007/11733836_27.
Chandramouli B, Yang J, Vahdat A. Distributed network querying with bounded approximate caching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2006 Jul 7;3882 LNCS:374–388.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

July 7, 2006

Volume

3882 LNCS

Start / End Page

374 / 388

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences