Tagged with: data management


PROPOSAL

Today many data sources are small low-powered and hardware-constrained devices such as mobile phones, wearable or self-driving smart platforms, etc. Edge computing is a broad term that refers to computations performed on such edge devices. It becomes increasingly important to enable techniques that get more value out of data at the edge rather than always sending the data to a remote and more …
Supervisors: Pınar Tözün, Robert Bayer
Semester: Fall 2023
Tags: resource-constrained hardware, data management, ML model updates, tinyML

PROPOSAL

Observing how well data-intensive systems utilize hardware resources is a crucial preliminary step to improve system performance and reduce hardware waste. To do such observations, one has to collect a lot of monitoring data on hardware behavior through experiments. In our group, we have recently built a framework to aid the management of such monitoring data efficiently, called Resource-Aware …
Supervisors: Pınar Tözün, Ties Robroek
Semester: Fall 2023
Tags: benchmarking, data management, data visualization

PROPOSAL

Today many data sources are small low-powered and hardware-constrained devices such as mobile phones, wearable or self-driving smart platforms, etc. Edge computing is a broad term that refers to computations performed on such edge devices. It becomes increasingly important to enable techniques that get more value out of data at the edge rather than always sending the data to a remote and more …
Supervisors: Pınar Tözün, Robert Bayer
Semester: Fall 2023
Tags: resource-constrained hardware, data management, resource management, tinyML

PROPOSAL

(This project will be carried out in collaboration with Xilinx Research Labs in Dublin) Machine Learning operators are becoming increasingly commonly used in data management systems and, in this project, we will explore the challenges and benefits of integrating inference operators from FINN [1] within a so-called Smart Storage system [2]. Both the inference and data management aspects will be …
Supervisors: Zsolt István
Semester: Spring 2021
Tags: FPGA, Data Management, MachineLearning

PROPOSAL

(This topic is going to be co-supervised by Bernardo Machado David [http://www.bmdavid.com/]) Database systems managing private data may leak sensitive information when queries are done in the clear, even if the data itself is encrypted. A recent line of research has looked into combining database engines supporting standard SQL queries with techniques for secure Multiparty Computation (MPC), …
Supervisors: Zsolt István
Semester: Spring 2021
Tags: Theoretical Computer Science, Data Management, Security and Privacy

PROPOSAL

Given a private database that I can access only through specific queries, there is still a lot I can learn on its entries [1]. Differential Privacy (DP) tackles this: letting me learn the (approximate) result of complex queries on a database, but preventing me from learning much about its specific entries. The basic approach of DP often boils down to: “apply a privacy-preserving transformation T …
Supervisors: Zsolt István
Semester: Spring 2021
Tags: Theoretical Computer Science, Data Management, Security and Privacy

PROPOSAL

Blockchains are often used synonymously with crypto-currencies and unspent transaction output (UTXO) data models, but there are emerging blockchain platforms that offer a more general data model and smart contracts that can manipulate this data freely (e.g. Hyperledger Fabric [1]). As such, these platforms resemble in many ways distributed databases, storing a collection of records, organized as …
Supervisors: Zsolt István
Semester: Spring 2021
Tags: Blockchain, Data Management, Benchmarking