Decentrally Coordinated Execution of Adaptations in Distributed Self-Adaptive Software Systems

Software systems in domains like Smart Cities, the Internet of Things or autonomous cars are coined by a high degree of distribution across several independent computing devices and the requirement to be able to adjust themselves to varying situations in their operational environment. Self-adaptive software systems are a natural choice to implement such context-dependent software systems. A multitude of approaches already implement self-adaptive systems and some consider even distribution aspects.Yet, none of the existing solutions supports the coordination of adaptation operations spanning multiple independent nodes, which is necessary to ensure a consistent adaptation even in presence of network errors or node failures. In this paper, we tackle this challenge to execute adaptations in distributed self-adaptive software systems in a coordinated manner. We present a protocol that enables the self-adaptive software system to execute correlated adaptations on multiple nodes in a transactional manner ensuring an atomic and consistent transition of the distributed system from its source to the desired target configuration. The protocol is validated to be free of deadlocks for any given adaptation at any point in time using a model-checking approach. The performance of our approach is investigated in experiments that emulate the protocol's execution on real devices for different sizes of distributed applications and adaptation scenarios

A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System

Self-adaptation is a promising approach to manage the complexity of modern software systems. A self-adaptive system is able to adapt autonomously to internal dynamics and changing conditions in the environment to achieve particular quality goals. Our particular interest is in decentralized self-adaptive systems, in which central control of adaptation is not an option. One important challenge in self-adaptive systems, in particular those with decentralized control of adaptation, is to provide guarantees about the intended runtime qualities. In this paper, we present a case study in which we use model checking to verify behavioral properties of a decentralized self-adaptive system. Concretely, we contribute with a formalized architecture model of a decentralized traffic monitoring system and prove a number of self-adaptation properties for flexibility and robustness. To model the main processes in the system we use timed automata, and for the specification of the required properties we use timed computation tree logic. We use the Uppaal tool to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432

Using status messages in the distributed test architecture

If the system under test has multiple interfaces/ports and these are physically distributed then in testing we place a tester at each port. If these testers cannot directly communicate with one another and there is no global clock then we are testing in the distributed test architecture. If the distributed test architecture is used then there may be input sequences that cannot be applied in testing without introducing controllability problems. Additionally, observability problems can allow fault masking. In this paper we consider the situation in which the testers can apply a status message: an input that causes the system under test to identify its current state. We show how such a status message can be used in order to overcome controllability and observability problems

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify and analyse a prominent example of adaptive system: robot swarms equipped with obstacle-avoidance self-assembly strategies. The analysis exploits the statistical model checker PVesta