Maria Isabel Catarino Couceiro
Autonomic Replicated Software Transactional Memory
Thesis submitted for the PhD in Computer Science and Engineering, Instituto Superior Técnico
(IST), Universidade de Lisboa
Abstract
Software Transactional Memory (STM) systems have emerged as a powerful
paradigm to develop concurrent applications. By sparing the programmer
from the burden of explicitly dealing with low-level concurrency
mechanisms, STMs increase the code reliability and shorten the
development time.
For scalability and fault-tolerance reasons, it is relevant to build
distributed implementations of this paradigm allowing the deployment
of transactional systems in environments such as the
cloud. Replication clearly plays a role of paramount importance in
these platforms, as it represents the key mechanism to ensure data
durability in face of unavoidable node failures. However, there is a
myriad of techniques to maintain the consistency of the replicated
data, each performing differently according to the workload and there
is no "one-size fits all" technique that achieves optimal performance
in any scenario. In addition, due to the growing complexity of these
systems and unpredictability of the workloads, manual management
becomes a complex, tiresome and error-prone task.
To circumvent these issues, this thesis investigates an autonomic
architecture for the replication of STMs that supports the change of
its replica consistency protocol according to the workload, in order
to provide the best throughput possible, using techniques that do not
require human intervention. First, it studies the use of machine
learning to support the autonomic management of the replica
consistency protocols. Then, the thesis presents a solution that
relies on two machine learning approaches to drive the adaptation in a
distributed STM that is able to switch between certification-based
protocols. Finally, it proposes a framework for autonomic distributed
STMs that supports multiple replica consistency protocols and two
switching mech- anisms: one forcing the system to stop processing
transactions while the protocol switch is in progress, and another
which allows the programmer to define how the two switching protocols
can co-exist during the transition period.
Selected Publications
- Autonomic Replicated Software Transactional Memory.
- Maria Isabel Catarino Couceiro
- PhD Thesis. Instituto Superior Técnico, Universidade de
Lisboa.
- July, 2015.
- Available BibTeX, PhD Thesis.
- Chasing the Optimum in Replicated In-memory
Transactional Platforms via Protocol Adaptation.
- M. Couceiro, P. Ruivo, P. Romano, L. Rodrigues.
- In IEEE
Transactions on Parallel and Distributed Systems
- Digital Object Identifier
no. 10.1109/TPDS.2014.2363460
- Chasing the Optimum in Replicated In-memory
Transactional Platforms via Protocol Adaptation.
- M. Couceiro, P. Ruivo, P. Romano, L. Rodrigues.
- Proceedings
of the 43rd Annual IEEE/IFIP International Conference on Dependable
Systems and Networks, Budapest, Hungary, June 2013.
-
Available BibTeX, abstract (html).
- PolyCert: Polymorphic Self-Optimizing Replication
for In-Memory Transactional Grids.
- M. Couceiro,
P. Romano and L. Rodrigues.
- In Proceedings of the ACM/IFIP/USENIX
12th International Middleware Conference, Lisboa, Portugal, December
2011.
- Available BibTeX, abstract (html) and report (pdf).
- A Machine Learning Approach to Performance
Prediction of Total Order Broadcast Protocols.
- M. Couceiro, Paolo Romano and L. Rodrigues.
- In proceedings
4th IEEE International Conference on Self-Adaptive and
Self-Organizing Systems (SASO), Budapest, Hungary, September 2010
- Available BibTeX, abstract (html) and report (pdf).
Luís Rodrigues