Distributed systems often serve dynamic workloads and resource demands evolve over time. Such a temporal behavior stands in contrast to the static and demand-oblivious nature of most data structures used by these systems. In this paper, we are particularly interested in consistent hashing, a fundamental building block in many large distributed systems. Our work is motivated by the hypothesis that a more adaptive approach to consistent hashing can leverage structure in the demand, and hence improve storage utilization and reduce access time. We initiate the study of demand-aware consistent hashing. Our main contribution is H&A, a constant-competitive online algorithm (i.e., it comes with provable performance guarantees over time). H&A is demand-aware and optimizes its internal structure to enable faster access times, while offering a high utilization of storage. We further evaluate H&A empirically.
@InProceedings{pourdamghani_et_al:LIPIcs.OPODIS.2024.24, author = {Pourdamghani, Arash and Avin, Chen and Sama, Robert and Shiran, Maryam and Schmid, Stefan}, title = {{Hash \& Adjust: Competitive Demand-Aware Consistent Hashing}}, booktitle = {28th International Conference on Principles of Distributed Systems (OPODIS 2024)}, pages = {24:1--24:23}, 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.2024.24}, URN = {urn:nbn:de:0030-drops-225607}, doi = {10.4230/LIPIcs.OPODIS.2024.24}, annote = {Keywords: Consistent hashing, demand-awareness, online algorithms} }
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