5 papers
Sig2Model: A Boosting-Driven Model for Updatable Learned Indexes
Alireza Heidari, Amirhossein Ahmad, Wei Zhang +1
Learned Indexes (LIs) represent a paradigm shift from traditional index structures by employing machine learning models to approximate the cumulative distribution function (CDF) of…
DobLIX: A Dual-Objective Learned Index for Log-Structured Merge Trees
Alireza Heidari, Amirhossein Ahmadi, Wei Zhang
In this paper, we introduce DobLIX, a dual-objective learned index specifically designed for Log-Structured Merge(LSM) tree-based key-value stores. Although traditional learned ind…
Globalization for Scalable Short-term Load Forecasting
Amirhossein Ahmadi, Hamidreza Zareipour, Henry Leung
Forecasting load in power transmission networks is essential across various hierarchical levels, from the system level down to individual points of delivery (PoD). While intuitive…
UpLIF: An Updatable Self-Tuning Learned Index Framework
Alireza Heidari, Amirhossein Ahmadi, Wei Zhang
The emergence of learned indexes has caused a paradigm shift in our perception of indexing by considering indexes as predictive models that estimate keys' positions within a data s…
MetaHive: A Cache-Optimized Metadata Management for Heterogeneous Key-Value Stores
Alireza Heidari, Amirhossein Ahmadi, Zefeng Zhi +1
Cloud key-value (KV) stores provide businesses with a cost-effective and adaptive alternative to traditional on-premise data management solutions. KV stores frequently consist of h…