Event Stream Processing (ESP) systems are very
popular in monitoring applications. Algorithmic trading, net-
work monitoring and sensor networks are good examples of
applications that rely upon ESP systems. As these systems
become larger and more widely deployed, they have to answer
increasingly stronger requirements that are often difficult to
satisfy. Fault-tolerance is a good example of such a non-
trivial requirement. Making ESP operators fault-tolerant can
add considerable performance overhead to the application.
In this paper, we focus on active replication as an approach
to provide fault-tolerance to ESP operators. More precisely,
we address the performance costs of active replication for
operators in distributed ESP applications. We use a speculation
mechanism based on Software Transactional Memory (STM) to
achieve the following goals: (i) enable replicas to make progress
using optimistic delivery; (ii) enable early forwarding of
speculative computation results; (iii) enable active replication
of multi-threaded operators using transactional executions.
Experimental evaluation shows that, using this combination of
mechanisms, one can implement highly efficient fault-tolerant
ESP operators.