Sorana Tania Nemes

Towards a Case-Based Reasoning Approach to Dynamic Adaptation for Large-Scale Distributed Systems

The ever growing demands from the software area have led to the development of large-scale distributed systems which bring together a wide pool of services and resources. Their composition and deployment come in different solutions tailored to users requests based on business models, functionality, quality of service, cost, and value. Bridging different parts into one software solution is brittle due to issues like heterogeneity, complexity, lack of transparency, network and communication failures, and misbehavior. The current paper proposes a decision-based solution for the dynamic adaptation part of a middleware which addresses the aforementioned problems for large-scale distributed systems. The envisioned architecture is built on case-based reasoning principles and stands at the base of the adaptation processes that are imperative for ensuring the delivery of high-quality software. The solution is further extended through ground models with a focus on reliability, availability of components, and failure tolerance in terms of abstract state machines. The novelty of the approach resides in making use of formal modeling for one of the emerging problems and introducing an adequate prototype, on top of which one can apply reasoning and verification methods.

Towards Modeling Adaptation Services for Large-Scale Distributed Systems with Abstract State Machines

The evolution of Large-Scale Distributed Systems favored the development of solutions for smart cities. Such systems face a high-level of uncertainty as they consist of a large number of sensors, processing centers, and services deployed along a wide geographical area. Bringing together different resources poses increased complexity as well as communication efforts, and introduces a large set of possible failures and challenges of continuously growing computational and storage expectations. In such a frame, the role of the adaptation components is vital for ensuring availability, reliability, and robustness. This paper introduces a formal approach for modeling and verifying the properties and behavior of the adaptation framework addressing the case of a system failure. We formalize the behavior and the collaboration mechanisms between agents of the system with the aid of Abstract State Machines and employ the ASMETA toolset for simulating and analyzing properties of the model.

Conceptual Modelling of Autonomous Multi-cloud Interaction with Reflective Semantics

Distributed systems that exploit software services from multiple clouds provide opportunities for software systems that address problems associated with systems of systems. In this paper we present an approach for the conceptual modelling of such systems, which is grounded in a distributed middleware that coordinates the client access to multiple clouds through a concept of mediator. Furthermore, each component of the middleware constitutes an abstract machine that is realised by three layers: a layer for normal operation, a layer for monitoring and detection of critical situations, and an adaptation layer, which in case of an identified anomaly changes the normal behaviour. The semantics of this autonomous system can be captured by linguistic reflection, for which reflective Abstract State Machines will be exploited.

An Event-B-based approach to hybrid systems engineering and its application to a hemodialysis machine case study

Abstract Systems engineering concerns the complete process for the development of complex systems comprising hardware, software, facilities and personnel. Such systems are hybrid, as some components are characterized by continuous behavior, whereas the behavior of others is discrete. In this paper we present a concise conceptual model for hybrid systems engineering with semantics grounded in a hybrid extension of Event-B. We show that structural modeling can be based on well-known concepts of the entity-relationship model requiring only some extensions to data types and constraints, while behavioral modeling requires a careful separation of synchronous and asynchronous interaction and high-level means for the integration of continuous functions. On these grounds we address the separation of concerns for continuous and hybrid components. The article uses a sophisticated industrial example of a hemodialysis machine to illustrate the modeling method.

Conceptual Modelling of Hybrid Systems

Complex systems comprising hardware, software, facilities and personnel are gaining more and more importance. Such systems are hybrid, as some components are characterised by continuous behaviour, whereas the behaviour of others is discrete. In this paper we present a concise conceptual model that is capable to capture structure and behaviour of such systems. We show that structural modelling can be based on well-known concepts of the entity-relationship model requiring only some extensions to constraints. We further show that behavioural modelling requires only a careful separation of synchronous and asynchronous interaction and high-level means for the integration of continuous functions. We show that all these concepts can be captured by defining a semantics in hybrid Event-B. The paper illustrates the modelling method by a sophisticated industrial example of a hemodialysis machine.

Towards Care Systems Using Model-Driven Adaptation and Monitoring of Autonomous Multi-clouds

In cloud computing, the ability to run and manage multi-cloud systems allows exploiting the peculiarities of each cloud solution and hence optimising the performance, availability, and cost of the applications. In this paper, we investigate the use case of a robotic care system as an application of autonomous multi-clouds. We present requirements and properties of an Abstract State Machines-based conceptual model that coordinates the multi-cloud interaction through the specification of a middleware exploiting adaptive interfaces to multiple clouds and supporting various service formats. While the multi-cloud system is running in normal mode, data about the execution will be gathered and evaluated by the monitoring component, and in case any critical situation is discovered the adaptation component is alerted. We show that for the care system this can be fruitfully exploited for failure alerts, failure anticipation and prevention, and safety hazards detection.

Management of accurate profile matching using multi-cloud service interaction

The current paper describes our research towards a cloud infrastructure for the universal access and interaction with a number of services implementing methods for enriching, matching and querying information about job offers and applicant profiles in the cloud. These methods exploit well-known recruitment knowledge bases in order to deliver valuable information to such organizations as public and private employment agencies that we assume to be geographically distributed. The rationale behind our approach is to offer an universal, yet inexpensive, distribution model able to reduce the cost of installing and maintaining the recruitment technology within the clients businesses.

Adopting Formal Approaches for Monitoring Sensors of Intercloud Systems

The coordination of resources offered by multiple cloud providers to the end users aims to improve the Quality of Service. However, such systems exhibit a higher complexity and heterogeneity, which need to be handled correctly. In a large network of sensors provided by an Intercloud, the role of the monitoring processes is to identify existing issues and further report them for reconfiguration. Faulty monitors might report nonexistent problems or neglect existing ones. Their correctness highly influences the reliability of the whole system. By formal modeling the monitoring processes, this paper aims to improve the robustness of the system and to capture fundamental properties of monitors. The Abstract State Machine formal method is used for creating the models, which follow a modular approach.