FINO: Achieving High-performance and Reliable Transaction/Analytical Processing for Enabling Financial Big-data Analytics in Edge Computing

PI: Dr. Heming Cui, HKU

Project Abstract: 

The edge computing and big-data computing paradigms are pushing more and more applications to deploy in edge datacenters (e.g., AWS Region and Azure Edge) in order to enable ultra low-latency data access for end users. Recently, the famous Gartner company predicted that, in around 2025, about 75% of enterprise data will be created and processed in edge datacenters — outside traditional core data centers (clouds). To conduct real-time actions and global-scale decisions, a real-world edge application (e.g., edge financial trading, smart- city scheduling robotics, and edge supply chain) usually desires stringent client-perceived latency (e.g., 99% tail latency) on processing both OLTP (OnLine Transactional Processing) transactions and real-time OLAP (OnLine Analytical Processing, or big-data processing) analytical queries. Furthermore, since edge devices (mobile phones and hosts in edge datacenters) are often owned or managed by diverse mutually untrusted enterprises, it is crucial to tolerate the reliability issues of both hardware failures and malicious behaviors (e.g., issuing forged transactions) in these devices. Therefore, this proposal aims to enhance performance and tackle both these two reliability issues as a whole.

This proposal will pursue three substantial objectives using a bottom-then-up methodology and create FINO (Freshness, Performance Isolation, Non-blocking, and One-round commit), the first high-performance and reliable HTAP system for edge computing. Dr Cui (the PI)’s preliminary results of this proposal have led to: (1) publications in international best-tiered (China Computer Federation, or CCF, A-class journals and conferences) academic venues (including ACM SOSP 2021, IEEE TDSC 2021, and Usenix ATC 2022); (2) an ITF Platform grant award (Dr. Cui is the PI, HK $3.3 million) in May 2022; and (3) commercial releases of Dr Cui’s UTEE (an HKU-invented big-data security system) on Huawei Clouds (see UTEE in https://www.huaweicloud.com/product/tics.html) and Huawei’s official commercialization acknowledgement letter (https://hemingcui.github.io/doc/utee-ack.pdf). This letter confirms that our HKU’s UTEE big-data security system is already usable by Huawei Clouds’ 3 million users in 170 countries.