Agent Based Test and Repair of Distributed Systems

This article demonstrates how to use intelligent agents for testing and repairing a distributed system, whose elements may or may not have embedded BIST (Built-In Self-Test) and BISR (Built-In Self-Repair) facilities. Agents are software modules that perform monitoring, diagnosis and repair of the faults. They form together a society whose members communicate, set goals and solve tasks. An experimental solution is presented, and future developments of the proposed approach are explore

Agent Based Test and Repair of Distributed Systems

This article demonstrates how to use intelligent agents for testing and repairing a distributed system, whose elements may or may not have embedded BIST (Built-In Self-Test) and BISR (Built-In Self-Repair) facilities. Agents are software modules that perform monitoring, diagnosis and repair of the faults. They form together a society whose members communicate, set goals and solve tasks. An experimental solution is presented, and future developments of the proposed approach are explored

Multi-Agent Cooperation for Particle Accelerator Control

We present practical investigations in a real industrial controls environment for justifying theoretical DAI (Distributed Artificial Intelligence) results, and we discuss theoretical aspects of practical investigations for accelerator control and operation. A generalized hypothesis is introduced, based on a unified view of control, monitoring, diagnosis, maintenance and repair tasks leading to a general method of cooperation for expert systems by exchanging hypotheses. This has been tested for task and result sharing cooperation scenarios. Generalized hypotheses also allow us to treat the repetitive diagnosis-recovery cycle as task sharing cooperation. Problems with such a loop or even recursive calls between the different agents are discussed

Solving DCOPs with Distributed Large Neighborhood Search

The field of Distributed Constraint Optimization has gained momentum in recent years, thanks to its ability to address various applications related to multi-agent cooperation. Nevertheless, solving Distributed Constraint Optimization Problems (DCOPs) optimally is NP-hard. Therefore, in large-scale, complex applications, incomplete DCOP algorithms are necessary. Current incomplete DCOP algorithms suffer of one or more of the following limitations: they (a) find local minima without providing quality guarantees; (b) provide loose quality assessment; or (c) are unable to benefit from the structure of the problem, such as domain-dependent knowledge and hard constraints. Therefore, capitalizing on strategies from the centralized constraint solving community, we propose a Distributed Large Neighborhood Search (D-LNS) framework to solve DCOPs. The proposed framework (with its novel repair phase) provides guarantees on solution quality, refining upper and lower bounds during the iterative process, and can exploit domain-dependent structures. Our experimental results show that D-LNS outperforms other incomplete DCOP algorithms on both structured and unstructured problem instances

Delivering knowledge in the field: A telecommunications service provision and maintenance case

This paper proposes a novel approach to providing knowledge management services in a business process wherein field engineers are the main process actors, providing and maintaining telecommunications services. Cooperating multi-agents play a central role for the provision of knowledge management services by integrating heterogeneous systems to collect related knowledge for the execution of mobile tasks. The proposed system is expected to increase both the performance of the mobile workforce and customer satisfaction by supporting and encouraging knowledge sharing

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

Self-healing composites: A review

Self-healing composites are composite materials capable of automatic recovery when damaged. They are inspired by biological systems such as the human skin which are naturally able to heal themselves. This paper reviews work on self-healing composites with a focus on capsule-based and vascular healing systems. Complementing previous survey articles, the paper provides an updated overview of the various self-healing concepts proposed over the past 15 years, and a comparative analysis of healing mechanisms and fabrication techniques for building capsules and vascular networks. Based on the analysis, factors that influence healing performance are presented to reveal key barriers and potential research directions