Cost-Oblivious Storage Reallocation

Author:

Bender Michael A.1,Farach-Colton Martín2,Fekete Sándor P.3ORCID,Fineman Jeremy T.4,Gilbert Seth5

Affiliation:

1. Stony Brook University, NY, USA

2. Rutgers University, NY, USA

3. TU Braunschweig, Braunschweig, Germany

4. Georgetown University, DC, USA

5. National University of Singapore, Singapore

Abstract

Databases allocate and free blocks of storage on disk. Freed blocks introduce holes where no data is stored. Allocation systems attempt to reuse such deallocated regions in order to minimize the footprint on disk. When previously allocated blocks cannot be moved, this problem is called the memory allocation problem. The competitive ratio for this problem has matching upper and lower bounds that are logarithmic in the number of requests and in the ratio of the largest to smallest requests. This article defines the storage reallocation problem, where previously allocated blocks can be moved, or reallocated , but at some cost. This cost is determined by the allocation/reallocation cost function . The objective is to minimize the storage footprint, that is, the largest memory address containing an allocated object, while simultaneously minimizing the reallocation costs. This article gives asymptotically optimal algorithms for storage reallocation, in which the storage footprint is at most (1+ ϵ) times optimal, and the reallocation cost is O ((1/ϵ)log (1/ϵ)) times the original allocation cost, that is, it is within a constant factor of optimal when ϵ is a constant. The algorithms are cost oblivious , which means they achieve these bounds with no knowledge of the allocation/reallocation cost function, as long as the cost function is subadditive.

Funder

Sandia National Laboratories

NSF

Research Group FOR 1800

MOE Tier 2

DFG

Controlling Concurrent Change

Publisher

Association for Computing Machinery (ACM)

Subject

Mathematics (miscellaneous)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Strongly History-Independent Storage Allocation: New Upper and Lower Bounds;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

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