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PrivacyPreserving Access of Outsourced Data via Oblivious RAM Simulation. ArXiv eprints, April 2011. Eprint 1007.1259v2
"... Suppose a client, Alice, has outsourced her data to an external storage provider, Bob, because he has capacity for her massive data set, of size n, whereas her private storage is much smaller—say, of size O(n1/r), for some constant r> 1. Alice trusts Bob to maintain her data, but she would like t ..."
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Suppose a client, Alice, has outsourced her data to an external storage provider, Bob, because he has capacity for her massive data set, of size n, whereas her private storage is much smaller—say, of size O(n1/r), for some constant r> 1. Alice trusts Bob to maintain her data, but she would like to keep its contents private. She can encrypt her data, of course, but she also wishes to keep her access patterns hidden from Bob as well. We describe schemes for the oblivious RAM simulation problem with a small logarithmic or polylogarithmic amortized increase in access times, with a very high probability of success, while keeping the external storage to be of size O(n). To achieve this, our algorithmic contributions include a parallel MapReduce cuckoohashing algorithm and an externalmemory dataoblivious sorting algorithm.
Hash Tables With Finite Buckets Are Less Resistant To Deletions
"... Abstract — We show that when memory is bounded, i.e. buckets are finite, dynamic hash tables that allow insertions and deletions behave significantly worse than their static counterparts that only allow insertions. This behavior differs from previous results in which, when memory is unbounded, the t ..."
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Abstract — We show that when memory is bounded, i.e. buckets are finite, dynamic hash tables that allow insertions and deletions behave significantly worse than their static counterparts that only allow insertions. This behavior differs from previous results in which, when memory is unbounded, the two models behave similarly. We show the decrease in performance in dynamic hash tables using several hashtable schemes. We also provide tight upper and lower bounds on the achievable overflow fractions in these schemes. Finally, we propose an architecture with contentaddressable memory (CAM), which mitigates this decrease in performance. A. Background I.
Efficient Dynamic Index Structure for Natural Number Intensive Application
"... Wide range of indexing techniques exists in the world of relational database. Speed of data insertion & retrieval depends on the type of query and available Indexing mechanism. Prevalent mechanisms lack in terms of spacetime efficiency and simple structure, for real time applications where the ..."
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Wide range of indexing techniques exists in the world of relational database. Speed of data insertion & retrieval depends on the type of query and available Indexing mechanism. Prevalent mechanisms lack in terms of spacetime efficiency and simple structure, for real time applications where the database system needs to handle queries like equality search & range search. Even for simple tasks like getting data by ID, a system imposes heavy resource utilization. For example, Applications such as, telephone directory, transaction information details in banking, status about railway reservation etc., backed with relational database system that employs complex structure like BTree or B+Tree. Hence in such cases, instead of those complex structures, if some lighter technique can be used, which can greatly enhance the overall performance in terms of memory usage and simpler in terms of working & implementation. The paper presents how the Proposed Technique can significantly impact the overall performance, if applied as Primary Indexing method for range search & equality search queries.
Maximum Bipartite Matching Size And Application to Cuckoo Hashing
"... Cuckoo hashing with a stash is a robust highperformance hashing scheme that can be used in many reallife applications. It complements cuckoo hashing by adding a small stash storing the elements that cannot fit into the main hash table due to collisions. However, the exact required size of the stas ..."
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Cuckoo hashing with a stash is a robust highperformance hashing scheme that can be used in many reallife applications. It complements cuckoo hashing by adding a small stash storing the elements that cannot fit into the main hash table due to collisions. However, the exact required size of the stash and the tradeoff between its size and the memory overprovisioning of the hash table are still unknown. We settle this question by investigating the equivalent maximum matching size of a random bipartite graph, with a constant leftside vertex degree d = 2. Specifically, we provide an exact expression for the expected maximum matching size and show that its actual size is close to its mean, with high probability. This result relies on decomposing the bipartite graph into connected components, and then separately evaluating the distribution of the matching size in each of these components. In particular, we provide an exact expression for any finite bipartite graph size and also deduce asymptotic results as the number of vertices goes to infinity. We also extend our analysis to cases where only part of the leftside vertices have a degree of 2; as well as to the case where the set of rightsize vertices is partitioned into two subsets, and each
Comparison of Hash Table Performance with Open Addressing and Closed Addressing: An Empirical Study
"... In this paper, we conducted empirical experiments to study the performance of hashing with a large set of data and compared the results of different collision approaches. The experiment results leaned more to closed addressing than to open addressing and deemed linear probing impractical due to its ..."
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In this paper, we conducted empirical experiments to study the performance of hashing with a large set of data and compared the results of different collision approaches. The experiment results leaned more to closed addressing than to open addressing and deemed linear probing impractical due to its low performance. Moreover, when items are randomly distributed with keys in a large space, different hash algorithms might produce similar performance. Increasing randomness in keys does not help hash table performance either and it seems that the load factor solely determines possibility of collision. These new discoveries might help programmers to design software products using hash tables.