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Brief Announcement: Demand-Aware Consistent Hashing with Bounded Loads & Greedy Routing

Authors Arash Pourdamghani , Chen Avin , Stefan Schmid

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Subject Classification

ACM Subject Classification
  • Theory of computation → Data structures design and analysis
Keywords
  • Consistent hashing
  • peer-to-peer networks
  • greedy routing

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Abstract

Workloads of networked and distributed systems are often far from random, but exhibit certain structure: they are skewed and bursty. Networked systems which can adapt to and exploit such spatial and temporal structure, in a demand-aware manner, bear the potential to be more efficient than their demand-oblivious alternatives. This paper studies demand-awareness in the context of consistent hashing, a fundamental component in many modern distributed systems. We present a novel demand-aware consistent hashing method to improve access time and storage utilization in distributed hash tables. In particular, the resulting system supports local (greedy) routing, ensures bounded server loads, and applies to various network topologies. We formally prove that our algorithms achieve a constant approximation ratio in the offline scenario.

Cite As Get BibTex

Arash Pourdamghani, Chen Avin, and Stefan Schmid. Brief Announcement: Demand-Aware Consistent Hashing with Bounded Loads & Greedy Routing. In 5th Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 373, pp. 24:1-24:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.SAND.2026.24

Author Details

Arash Pourdamghani
  • TU Berlin, Germany
Chen Avin
  • Ben-Gurion University of the Negev, Beer Sheva, Israel
Stefan Schmid
  • TU Berlin, Germany
  • Weizenbaum Institute, Berlin, Germany
  • Fraunhofer SIT, Berlin, Germany

Funding

This project has received funding from the European Research Council (ERC), Proof-of-Concept project, FortifyNet (grant 101287293), 2026-2027. Chen Avin received funding from the Israel Science Foundation (ISF) grant no. 2497/23.

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