Cuckoo hashing

Pagh, Rasmus; Rodler, Flemming Friche

doi:10.1016/j.jalgor.2003.12.002

Cited by 827 publications

(328 citation statements)

References 27 publications

(47 reference statements)

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“…The case of d = 2 choices is notably different from that for other values of d and the theory for the case where there are d = 2 bucket choices for each item is well understood at this point [9,20,22]. We will therefore assume that d ≥ 3.…”

Section: Introductionmentioning

confidence: 99%

Maximum matchings in random bipartite graphs and the space utilization of Cuckoo Hash tables

Frieze

Melsted

2012

Random Struct Algorithms

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We study the the following question in Random Graphs. We are given two disjoint sets L, R with |L| = n = αm and |R| = m. We construct a random graph G by allowing each x ∈ L to choose d random neighbours in R. The question discussed is as to the size µ(G) of the largest matching in G. When considered in the context of Cuckoo Hashing, one key question is as to when is µ(G) = n whp? We answer this question exactly when d is at least three. We also establish a precise threshold for when Phase 1 of the Karp-Sipser Greedy matching algorithm suffices to compute a maximum matching whp.

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Section: Introductionmentioning

confidence: 99%

Maximum matchings in random bipartite graphs and the space utilization of Cuckoo Hash tables

Frieze

Melsted

2012

Random Struct Algorithms

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“…This phenomenon was experimentally observed long ago in the setting of Bloom filters [31]; other reported examples include [6,10,26,30,32]. Thus, it does not seem truly necessary to use the more complex hash functions for which this kind of performance can be proven.…”

Section: Introductionmentioning

confidence: 88%

“…There are other variations on this scheme, including the asymmetric version due to Vöcking [41] and cuckoo hashing [26]; we choose to study the original setting for simplicity.…”

Section: Balanced Allocationsmentioning

confidence: 99%

“…But a T -wise independent hash function mapping to {0, 1} m requires at least T · m bits to represent, which is often too large. For some applications, it has been shown that less independence, such as O(log T )-wise independence, suffices, e. g., [36,26], but such functions are still substantially less efficient than 2-universal hash functions. A series of works [38,24,11] have improved the time complexity of (almost) T -wise independence to a constant number of word operations, but the space complexity necessarily remains at least T · m.…”

Section: Introductionmentioning

confidence: 99%

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Chung¹,

Mitzenmacher²,

Vadhan³

2013

Theory of Comput.

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“…An encrypted cuckoo table [25,20] consists of three arrays (T 1 , T 2 , S) that hold ciphertexts of some fixed length. The arrays T 1 and T 2 are both of size m and serve as cuckoo-hash tables while S is an array of size s and serves as an auxiliary stash.…”

Section: Technical Toolsmentioning

confidence: 99%

Dynamic Proofs of Retrievability Via Oblivious RAM

2015

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Proofs of retrievability allow a client to store her data on a remote server (e.g., "in the cloud") and periodically execute an efficient audit protocol to check that all of the data is being maintained correctly and can be recovered from the server. For efficiency, the computation and communication of the server and client during an audit protocol should be significantly smaller than reading/transmitting the data in its entirety. Although the server is only asked to access a few locations of its storage during an audit, it must maintain full knowledge of all client data to be able to pass.Starting with the work of Juels and Kaliski (CCS '07), all prior solutions to this problem crucially assume that the client data is static and do not allow it to be efficiently updated. Indeed, they all store a redundant encoding of the data on the server, so that the server must delete a large fraction of its storage to 'lose' any actual content. Unfortunately, this means that even a single bit modification to the original data will need to modify a large fraction of the server storage, which makes updates highly inefficient. Overcoming this limitation was left as the main open problem by all prior works.In this work, we give the first solution providing proofs of retrievability for dynamic storage, where the client can perform arbitrary reads/writes on any location within her data by running an efficient protocol with the server. At any point in time, the client can execute an efficient audit protocol to ensure that the server maintains the latest version of the client data. The computation and communication complexity of the server and client in our protocols is only polylogarithmic in the size of the client's data. The starting point of our solution is to split up the data into small blocks and redundantly encode each block of data individually, so that an update inside any data block only affects a few codeword symbols. The main difficulty is to prevent the server from identifying and deleting too many codeword symbols belonging to any single data block. We do so by hiding where the various codeword symbols for any individual data block are stored on the server and when they are being accessed by the client, using the algorithmic techniques of oblivious RAM.

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Cuckoo hashing

Cited by 827 publications

References 27 publications

Maximum matchings in random bipartite graphs and the space utilization of Cuckoo Hash tables

Maximum matchings in random bipartite graphs and the space utilization of Cuckoo Hash tables

Untitled

Dynamic Proofs of Retrievability Via Oblivious RAM

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