2 Search Results for "Kassner, Yaron"

Document
DOI: 10.4230/LIPIcs.OPODIS.2024.23
Distributed Recoverable Sketches

Authors: Diana Cohen, Roy Friedman, and Rana Shahout

Published in: LIPIcs, Volume 324, 28th International Conference on Principles of Distributed Systems (OPODIS 2024)

Abstract
Sketches are commonly used in computer systems and network monitoring tools to provide efficient query executions while maintaining a compact data representation. Switches and routers maintain sketches to track statistical characteristics of the network traffic. The availability of such data is essential for the network analysis as a whole. Consequently, being able to recover sketches is critical following a switch crash. In this paper, we explore how nodes in a network environment can cooperate to recover sketch data whenever any of them crashes. In particular, we focus on frequency estimation linear sketches, such as the Count-Min Sketch. We consider various approaches to ensure data reliability and explore the trade-offs between space consumption, runtime overheads, and traffic during recovery, which we point out as design guidelines. Besides different aspects of efficacy, we design a modular system for ease of maintenance and further scaling. A key aspect we examine is how nodes update each other about their sketch content as it evolves over time. In particular, we compare between periodic full updates vs. incremental updates. We also examine several data structures to economically represent and encode a batch of latest changes. Our framework is generic, and other data structures can be plugged-in via an abstract API as long as they implement the corresponding API methods.
Cite as

Diana Cohen, Roy Friedman, and Rana Shahout. Distributed Recoverable Sketches. In 28th International Conference on Principles of Distributed Systems (OPODIS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 324, pp. 23:1-23:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{cohen_et_al:LIPIcs.OPODIS.2024.23,
  author =	{Cohen, Diana and Friedman, Roy and Shahout, Rana},
  title =	{{Distributed Recoverable Sketches}},
  booktitle =	{28th International Conference on Principles of Distributed Systems (OPODIS 2024)},
  pages =	{23:1--23:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-360-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{324},
  editor =	{Bonomi, Silvia and Galletta, Letterio and Rivi\`{e}re, Etienne and Schiavoni, Valerio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2024.23},
  URN =		{urn:nbn:de:0030-drops-225594},
  doi =		{10.4230/LIPIcs.OPODIS.2024.23},
  annote =	{Keywords: Sketches, Stream Processing, Distributed Recovery, Incremental Updates, Sketch Partitioning}
}
Document
DOI: 10.4230/LIPIcs.SWAT.2016.11
Efficient Summing over Sliding Windows

Authors: Ran Ben Basat, Gil Einziger, Roy Friedman, and Yaron Kassner

Published in: LIPIcs, Volume 53, 15th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2016)

Abstract
This paper considers the problem of maintaining statistic aggregates over the last W elements of a data stream. First, the problem of counting the number of 1's in the last W bits of a binary stream is considered. A lower bound of Omega(1/epsilon + log(W)) memory bits for Wepsilon-additive approximations is derived. This is followed by an algorithm whose memory consumption is O(1/epsilon + log(W)) bits, indicating that the algorithm is optimal and that the bound is tight. Next, the more general problem of maintaining a sum of the last W integers, each in the range of {0, 1, ..., R}, is addressed. The paper shows that approximating the sum within an additive error of RW epsilon can also be done using Theta(1/epsilon + log(W)) bits for epsilon = Omega(1/W). For epsilon = o(1/W), we present a succinct algorithm which uses B(1 + o(1)) bits, where B = Theta(W*log(1/(W*epsilon))) is the derived lower bound. We show that all lower bounds generalize to randomized algorithms as well. All algorithms process new elements and answer queries in O(1) worst-case time.
Cite as

Ran Ben Basat, Gil Einziger, Roy Friedman, and Yaron Kassner. Efficient Summing over Sliding Windows. In 15th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 53, pp. 11:1-11:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

Copy BibTex To Clipboard

@InProceedings{benbasat_et_al:LIPIcs.SWAT.2016.11,
  author =	{Ben Basat, Ran and Einziger, Gil and Friedman, Roy and Kassner, Yaron},
  title =	{{Efficient Summing over Sliding Windows}},
  booktitle =	{15th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2016)},
  pages =	{11:1--11:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-011-8},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{53},
  editor =	{Pagh, Rasmus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SWAT.2016.11},
  URN =		{urn:nbn:de:0030-drops-60241},
  doi =		{10.4230/LIPIcs.SWAT.2016.11},
  annote =	{Keywords: Streaming, Statistics, Lower Bounds}
}
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