Publications de Odysseas Papapetrou

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Anastasia Ailamaki, Raja Appuswamy, Matthaios Alexandros Olma, Odysseas Papapetrou

Current Approximate Query Processing (AQP) engines are far from silver-bullet solutions, as they adopt several static design decisions that target specific workloads and deployment scenarios. Offline AQP engines target deployments with large storage budget ...

IEEE2019

Data stream statistics over sliding windows: How to summarize 150 Million updates per second on a single node

Odysseas Papapetrou, Grigorios Chrysos, Dionysios Pnevmatikatos

Traditional data management systems map information using centralized and static data structures. Modern applications need to process in real time datasets much larger than system memory. To achieve this, they use dynamic entities that are updated with str ...

2019

Practical Private Range Search in Depth

Odysseas Papapetrou, Ioannis Demertzis

We consider a data owner that outsources its dataset to an untrusted server. The owner wishes to enable the server to answer range queries on a single attribute, without compromising the privacy of the data and the queries. There are several schemes on “pr ...

2018

Monitoring distributed fragmented skylines

Odysseas Papapetrou

Distributed skyline computation is important for a wide range of domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is ...

2018

Practical Private Range Search Revisited

Odysseas Papapetrou, Ioannis Demertzis

We consider a data owner that outsources its dataset to an untrusted server. The owner wishes to enable the server to answer range queries on a single attribute, without compromising the privacy of the data and the queries. There are several schemes on "pr ...

2016