TY - JOUR
T1 - InfiniStore
T2 - 49th International Conference on Very Large Data Bases, VLDB 2023
AU - Zhang, Jingyuan
AU - Newman, Nicholas John
AU - Wang, Ao
AU - Anwar, Ali
AU - Skourtis, Dimitrios
AU - Ma, Xiaolong
AU - Rupprecht, Lukas
AU - Yan, Feng
AU - Cheng, Yue
AU - Carver, Benjamin
AU - Tarasov, Vasily
N1 - Publisher Copyright:
© 2023, VLDB Endowment. All rights reserved.
PY - 2023
Y1 - 2023
N2 - Cloud object storage such as AWS S3 is cost-effective and highly elastic but relatively slow, while high-performance cloud storage such as AWS ElastiCache is expensive and provides limited elasticity. We present a new cloud storage service called ServerlessMemory, which stores data using the memory of serverless functions. ServerlessMemory employs a sliding-window-based memory management strategy inspired by the garbage collection mechanisms used in the programming language to effectively segregate hot/cold data and provides fine-grained elasticity, good performance, and a pay-per-access cost model with extremely low cost. We then design and implement InfiniStore, a persistent and elastic cloud storage system, which seamlessly couples the function-based ServerlessMemory layer with a persistent, inexpensive cloud object store layer. InfiniStore enables durability despite function failures using a fast parallel recovery scheme built on the auto-scaling functionality of a FaaS (Function-as-a-Service) platform. We evaluate InfiniStore extensively using both microbenchmarking and two real-world applications. Results show that InfiniStore has more performance benefits for objects larger than 10 MB compared to AWS ElastiCache and Anna, and InfiniStore achieves 26.25% and 97.24% tenant-side cost reduction compared to InfiniCache and ElastiCache, respectively.
AB - Cloud object storage such as AWS S3 is cost-effective and highly elastic but relatively slow, while high-performance cloud storage such as AWS ElastiCache is expensive and provides limited elasticity. We present a new cloud storage service called ServerlessMemory, which stores data using the memory of serverless functions. ServerlessMemory employs a sliding-window-based memory management strategy inspired by the garbage collection mechanisms used in the programming language to effectively segregate hot/cold data and provides fine-grained elasticity, good performance, and a pay-per-access cost model with extremely low cost. We then design and implement InfiniStore, a persistent and elastic cloud storage system, which seamlessly couples the function-based ServerlessMemory layer with a persistent, inexpensive cloud object store layer. InfiniStore enables durability despite function failures using a fast parallel recovery scheme built on the auto-scaling functionality of a FaaS (Function-as-a-Service) platform. We evaluate InfiniStore extensively using both microbenchmarking and two real-world applications. Results show that InfiniStore has more performance benefits for objects larger than 10 MB compared to AWS ElastiCache and Anna, and InfiniStore achieves 26.25% and 97.24% tenant-side cost reduction compared to InfiniCache and ElastiCache, respectively.
UR - http://www.scopus.com/inward/record.url?scp=85159469348&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159469348&partnerID=8YFLogxK
U2 - 10.14778/3587136.3587139
DO - 10.14778/3587136.3587139
M3 - Conference article
AN - SCOPUS:85159469348
SN - 2150-8097
VL - 16
SP - 1629
EP - 1642
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 7
Y2 - 28 August 2023 through 1 September 2023
ER -