Smash: Flexible, Fast, and Resource-efficient Placement and Lookup of Distributed Storage

Appeared in Proceedings of the ACM on Measurement and Analysis of Computing Systems .

Abstract

Large-scale distributed storage systems, such as object stores, usually apply hashing-based placement and lookup methods to achieve scalability and resource efficiency. However, when object locations are determined by hash values, placement becomes inflexible, failing to optimize or satisfy application requirements such as load balance, failure tolerance, parallelism, and network/system performance. This work presents a novel solution to achieve the best of two worlds: flexibility while maintaining cost-effectiveness and scalability. The proposed method Smash is an object placement and lookup method that achieves full placement flexibility, balanced load, low resource cost, and short latency. Smash utilizes a recent space-efficient data structure and applies it to object-location lookups. We implement Smash as a prototype system and evaluate it in a public cloud. The analysis and experimental results show that Smash achieves full placement flexibility, fast storage operations, fast recovery from node dynamics, and lower DRAM cost (<60%) compared to existing hash-based solutions such as Ceph and MapX.

Publication date:
May 2023

Authors:
Yi Liu
Shouqian Shi
Minghao Xie
Heiner Litz
Chen Qian

Projects:

Available media

Full paper text: PDF

Bibtex entry

@article{SIGMETRICS-Liu-2023,
  author       = {Yi Liu and Shouqian Shi and Minghao Xie and Heiner Litz and Chen Qian},
  title        = {Smash: Flexible, Fast, and Resource-efficient Placement and Lookup of Distributed Storage},
  journal      = {Proceedings of the ACM on Measurement and Analysis of Computing Systems},
  volume       = {},
  month        = may,
  year         = {2023},
}