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About

About

I collaborated on the European Community-funded GORDA project, whose goal was to foster database replication as a means to address the challenges of current database systems. I worked on providing GORDA with a web-based graphical monitoring and management console that leverages JMX capabilities. 

I was also involved in the P-SON project, specifically in developing applications for the NeEM epidemic multicast protocol. In this context, I worked on a RSS feed caching and dissemination architecture that leverages p2p networks to accomplish its task and later on a generic P2P content-push architecture based on Web feeds and social network services, which served as a basis for my Master’s dissertation work. I also worked on an epidemic dissemination protocol that takes advantage of participants’ shared interests without actually disclosing them. 

In the context of my Ph.D, my work was focused on how to bridge the gap between traditional database-centric applications and the promises of high availability. 

Currently, I'm a part of the CloudDBAppliance european project, and also have been collaborating with CPES in the context of the UPGRID and InteGRID european projects. 

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Details

Details

  • Name

    Ana Nunes Alonso
  • Cluster

    Computer Science
  • Role

    Researcher
  • Since

    01st February 2012
Publications

2017

Towards new data management platforms for a DSO as market enabler – UPGRID Portugal demo

Authors
Alonso, A; Couto, R; Pacheco, H; Bessa, R; Gouveia, C; Seca, L; Moreira, J; Nunes, P; Matos, PG; Oliveira, A;

Publication
CIRED - Open Access Proceedings Journal

Abstract

2013

Improving transaction abort rates without compromising throughput through judicious scheduling

Authors
Nunes, A; Pereira, J;

Publication
Proceedings of the ACM Symposium on Applied Computing

Abstract
Althought optimistic concurrency control protocols have increasingly been used in distributed database management systems, they imply a trade-off between the number of transactions that can be executed concurrently, hence, the peak throughput, and transactions aborted due to conflicts. We propose a novel optimistic concurrency control mechanism that controls transaction abort rate by minimizing the time during which transactions are vulnerable to abort, without compromising throughput. Briefly, we throttle transaction execution with an adaptive mechanism based on the state of the transaction queues while allowing out-of-order execution based on expected transaction latency. Preliminary evaluation shows that this provides a substantial improvement in committed transaction throughput. Copyright 2013 ACM.

2013

AJITTS: Adaptive just-in-time transaction scheduling

Authors
Nunes, A; Oliveira, R; Pereira, J;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
Distributed transaction processing has benefited greatly from optimistic concurrency control protocols thus avoiding costly fine-grained synchronization. However, the performance of these protocols degrades significantly when the workload increases, namely, by leading to a substantial amount of aborted transactions due to concurrency conflicts. Our approach stems from the observation that when the abort rate increases with the load as already executed transactions queue for longer periods of time waiting for their turn to be certified and committed. We thus propose an adaptive algorithm for judiciously scheduling transactions to minimize the time during which these are vulnerable to being aborted by concurrent transactions, thereby reducing the overall abort rate. We do so by throttling transaction execution using an adaptive mechanism based on the locally known state of globally executing transactions, that includes out-of-order execution. Our evaluation using traces from the industry standard TPC-E workload shows that the amount of aborted transactions can be kept bounded as system load increases, while at the same time fully utilizing system resources and thus scaling transaction processing throughput. © 2013 IFIP International Federation for Information Processing.