A Distributed Abstraction Algorithm for Online Predicate Detection

Abstract

Abstract-Analyzing a distributed computation is a hard problem in general due to the combinatorial explosion in the size of the state-space with the number of processes in the system. By abstracting the computation, unnecessary state explorations can be avoided. Computation slicing is an approach for abstracting distributed computations with respect to a given predicate. We focus on regular predicates, a family of predicates that covers many commonly used predicates for runtime verification. The existing algorithms for computation slicing are centralized -a single process is responsible for computing the slice in either offline or online manner. In this paper, we present first distributed online algorithm for computing the slice of a distributed computation with respect to a regular predicate. Our algorithm distributes the work and storage requirements across the system, thus reducing the space and computation complexity per process.

Runtime Verification for Decentralised and Distributed Systems

“…The so-called computation slices can be used for a more efficient detection (see Mittal et al [79], Alagar and Venkatesan [1], Chauhan et al [30]). Computation slices are abstractions of the distributed computation that guarantee the following: the predicate is present in a slice of a computation c if the predicate occurred in some state of c. This approximation is precise enough to detect the predicate.…”

“…Computation slices are abstractions of the distributed computation that guarantee the following: the predicate is present in a slice of a computation c if the predicate occurred in some state of c. This approximation is precise enough to detect the predicate. If an algorithm is too general and does not exploit the structure of the predicate under consideration, predicate detection can involve a long runtime and large memory overhead (Chauhan et al [30]). Hence, best current solutions for predicate detection consider only fragments of the possible space of global predicates (for example the so-called linear, relational, regular and co-regular, and stable fragments) to gain efficiency.…”

“…Hence, best current solutions for predicate detection consider only fragments of the possible space of global predicates (for example the so-called linear, relational, regular and co-regular, and stable fragments) to gain efficiency. Even though most techniques for predicate detection (Cooper and Marzullo [37], Mittal et al [79], Alagar and Venkatesan [1]) send all local events to a central process for inspection of its interleavings, some modern approaches (see Chauhan et al [30]) consider purely distributed detection. Based on Chauhan et al [30], Mostafa and Bonakdarpour [80] adapt the work to check whether properties defined using LTL are satisfied.…”

“…The first distributed solution to slice-based predicate detection is by Chauhan et al [30]. The solution is online and distributed, in the sense that the slicing is computed by the distributed monitors.…”

On the Number of Opinions Needed for Fault-Tolerant Run-Time Monitoring in Distributed Systems

“…Later, [9] uses a specialized parallel architecture (GPU), to implement runtime formal verification in a parallel fashion. Efficient automatic signaling monitoring in multi-core processors is considered in [13].…”