Dynamic Monitoring in PANGEA Platform Using Event-Tracing Mechanisms

The use of distributed multi-agent systems (MAS) have increased in recent years, with the growing potential to handle large volumes of data and coordinate the operations of many organizations. In these systems, each agent independently handles a set of specialized tasks and cooperates to achieve the goals of the system and a high degree of flexibility. Multi-agent systems have become the most effective and widely used form of developing this type of application in which communication among various devices must be both reliable and efficient. One of the problems related to distribute computing is message passing, which is related to the interaction and coordination among intelligent agents. Consequently, a multi-agent architecture must necessarily provide a robust communication platform and control mechanisms. This paper presents the integration of an event-tracing model in an agent platform called PANGEA. Adding this new capability, the platform allows improving the monitoring and analysis of the information that agents can send/receive in order to fulfil their goals more efficiently

Checking bounded reachability in asynchronous systems by symbolic event tracing

This report presents a new symbolic technique for checking reachability properties of asynchronous systems by reducing the problem to satisfiability in restrained difference logic. The analysis is bounded by fixing a finite set of potential events, each of which may occur at most once in any order. The events are specified using high-level Petri nets. The logic encoding describes the space of possible causal links between events rather than possible sequences of states as in Bounded Model Checking. Independence between events is exploited intrinsically without partial order reductions, and the handling of data is symbolic. On a family of benchmarks, the proposed approach is consistently faster than Bounded Model Checking. In addition, this report presents a compact encoding of the restrained subset of difference logic in propositional logic

Hardware-assisted software event tracing

Event tracing is a reliable and a low-intrusiveness method to debug and optimize systems and processes. Low overhead is particularly important in embedded systems where resources and energy consumption is critical. The most advanced tracing infrastructures achieve a very low footprint on the traced software, bringing each tracepoint overhead to less than a microsecond. To reduce this still non-negligible impact, the use of dedicated hardware resources is promising. In this paper, we propose complementary methods for tracing that rely on hardware modules to assist software tracing. We designed solutions to take advantage of CoreSight STM, CoreSight ETM, and Intel BTS, which are present on most newer ARM-based systems-on-chip and Intel x86 processors. Our results show that the time overhead for tracing can be reduced by up to 10 times when assisted by hardware, as compared to software tracing with LTTng, a high-performance tracer for Linux. We also propose a modification to the Perf tool to speed BTS execution tracing up to 65%

Model-driven performance evaluation for service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised for the empirical performance evaluation of model-driven developed service systems

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services