ELICA: <u>E</u>fficient and <u>L</u>oad Balanced <u>I</u>/O <u>C</u>ache <u>A</u>rchitecture for Hyperconverged Infrastructures
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hyperconverged Infrastructures</i> (HCIs) combine processing and storage elements to meet the requirements of data-intensive applications in performance, scalability, and quality of service. As an emerging paradigm, HCI should couple with a variety of traditional performance improvement approaches such as I/O caching in virtualized platforms. Contemporary I/O caching schemes are optimized for traditional single-node storage architectures and suffer from two major shortcomings for multi-node architectures: a) imbalanced cache space requirement and b) imbalanced I/O traffic and load. This makes existing schemes inefficient in distributing cache resources over an array of separate physical nodes. In this paper, we propose an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>E</u>fficient and <u>L</u>oad Balanced <u>I</u>/O <u>C</u>ache <u>A</u>rchitecture</i> (ELICA), managing the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">solid-state drive</i> (SSD) cache resources across HCI nodes to enhance I/O performance. ELICA dynamically reconfigures and distributes the SSD cache resources throughout the array of HCI nodes and also balances the network traffic and I/O cache load by dynamic reallocation of cache resources. To maximize the performance, we further present an optimization problem defined by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Integer Linear Programming</i> to efficiently distribute cache resources and balance the network traffic and I/O cache relocations. Our experimental results on a real platform show that ELICA improves quality of service in terms of average and worst-case latency in HCIs by 3.1× and 23%, respectively, compared to the state-of-the-art.
Authors
- André Brinkmann (ORCID: https://orcid.org/0000-0003-3083-2775)
- Reza Salkhordeh (ORCID: https://orcid.org/0000-0003-3786-7102)
- S. Farzad Ahmadi (ORCID: https://orcid.org/0000-0001-8622-1434)
- Onur Mutlu (ORCID: https://orcid.org/0000-0002-0075-2312)
- Zdeněk Bečvář (ORCID: https://orcid.org/0000-0001-5155-8192)
- Saba Ahmadian (ORCID: https://orcid.org/0000-0003-3625-9631)
- Mostafa Kishani (ORCID: https://orcid.org/0000-0002-1900-9916)
- Hossein Asadi (ORCID: https://orcid.org/0000-0002-0264-3865)
Institutions
- Sharif University of Technology (IR)
- Johannes Gutenberg University Mainz (DE)
- ETH Zurich (CH)
- Czech Technical University in Prague (CZ)
Publication Details
- Journal
- IEEE Transactions on Parallel and Distributed Systems
- Published
- 2025-07-24
- DOI
- https://doi.org/10.1109/tpds.2025.3592275
- Primary Topic
- Water Systems and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00