Khalil Drira

A QoS-Oriented Reconfigurable Middleware for Self-Healing Web Services

Maintaining the Quality of Service (QoS) is important for self-healing web service-based distributed interactive applications. It requires the ability to deal with permanently changing constraints both at the communication and the execution levels. Preventing or repairing QoS degradation also requires the capacity of identifying its possible or actual sources and the capacity of reconfiguration decision and enforcement. Dealing with these issues is especially challenging for web services since the self-healing solution has to preserve the dynamic composition property and to be seamless for the service requesters, while being always usable under the different deployment constraints. In this paper, we present a self-healing middleware framework able to provide the self-healing properties for QoS management in web service-based distributed interactive applications. The framework implementation has been achieved in the context of the WS-DIAMOND project. It covers the whole cycle of adaptation management including monitoring and analysis of QoS values, and substitution-based reconfiguration.

Architecting information centric ETSI-M2M systems

The European Telecommunications Standards Institute (ETSI) released a set of specifications to define a restful architecture for enabling seamless service provisioning across heterogeneous Machine-to-Machine (M2M) systems. The current version of this architecture is strongly centralized, thus requiring new enhancements to its scalability, fault tolerance, and flexibility. To bridge this gap, herein it is presented an Overlay Service Capability Layer, based on Information Centric Networking design. Key features, example use cases and preliminary performance assessments are also discussed to highlight the potential of our approach.

Toward semantic interoperability in oneM2M architecture

The oneM2M standard is a global initiative led jointly by major standards organizations around the world in order to develop a unique architecture for M2M communications. Prior standards, and also oneM2M, while focusing on achieving interoperability at the communication level, do not achieve interoperability at the semantic level. An expressive ontology for IoT called IoT-O is proposed, making best use of already defined ontologies in specific domains such as sensor, observation, service, quantity kind, units, or time. IoT-O also defines some missing concepts relevant for IoT such as thing, node, actuator, and actuation. The extension of the oneM2M standard to support semantic data interoperability based on IoT-O is discussed. Finally, through comprehensive use cases, benefits of the extended standard are demonstrated, ranging from heterogeneous device interoperability to autonomic behavior achieved by automated reasoning.

A QoS-Driven Reconfiguration Management System Extending Web Services with Self-Healing Properties

This paper addresses QoS management for self-healing Web services. The objective is to provide a healing framework based on service monitoring and architectural-level repair actions. We address these topics in the context of the European project WS-DIAMOND. We implemented and assessed a connector-based healing layer capable of intercepting, analyzing and enhancing SOAP traffic and message contents with QoS data. Our framework supports Service Monitoring and dynamic run-time reconfiguration based on reflective programming.

Describing dynamic software architectures using an extended UML model

In this paper, we propose a new UML2.0 profile to describe the change of software architectures. The profile introduces a set of stereotypes for modeling the structural and the dynamic aspect as well as architectural constraints. We adapt the component diagrams metamodel on specific purposes by extending existing metaclasses. The adaptations are defined using stereotypes which are grouped in a profile. The profile offers to the architects an intuitive and complete way to specify the software architecture based on visual notations.

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients’ health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the “Knowledge as a Service” approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

Autonomic computing system for self-management of machine-to-machine networks

The internet of things consists of a high amount of heterogeneous objects that are widely distributed and evolve frequently according to their context changes. Management of such a complex environment is costly in terms of time and money. Machine to Machine (M2M) networks will soon become virtually impossible to administer. Designing context aware autonomic system for M2M networks with capability of self-management is a challenge. This paper proposes an autonomic computing system based on standardized M2M architecture and composed of generic and extensible autonomic managers. Autonomic managers communicate with each other to enable self-management of application, service and communication layers based on knowledge models and reasoning rules. A smart metering use case is experimented to illustrate the proposed solution.

A model-driven adaptive approach for collaborative ubiquitous systems

Ubiquitous communicating systems have particular characteristics, such as their dynamic nature and the great number of users and heterogeneous devices involved. In our work, we focus on collaborative activities. For such activities, users are organized into groups and communicate in order to achieve a common goal. Therefore, the problem of designing and implementing collaborative applications on top of ubiquitous communicating systems is a complex task that requires adequate modeling. In our view, addressing this problem needs a model-driven approach in order to ensure the coherence and correctness of the built systems. In this paper, we propose a multi-level modeling approach for collaborative ubiquitous systems. Moreover, relevant abstraction levels are identified and means are provided for inter-level model transformation (refinement) and for adaptation to context changes (selection). This adaptation is guided by both high level requirements and low level constraints.

A Comprehensive Ontology-Based Approach for SLA Obligations Monitoring

Specifying clear quality of service (QoS) agreements between service providers and consumers is particularly important for the successful deployment of service-oriented architectures. The related challenges include correctly elaborating and monitoring QoS contracts (SLA: service level agreement) to detect and handle their violations. In this paper, first, we study and analyze existing SLA-related models. Then, we elaborate a complete, generic and semantically richer ontology-based model of SLA. We used the Semantic Web Rule Language (SWRL) to express SLA obligations in our model. This language facilitates the SLA monitoring process and the eventual action triggering in case of violations. We used this model to automatically generate semantic-enabled QoS obligations monitors. We have also developed a prototype to validate our model and our monitoring approach. Finally, we believe that this work is a step ahead to the total automation of the SLA management process.

A rule-driven approach for architectural self adaptation in collaborative activities using graph grammars

Architectural adaptation is important for handling self-configuring properties of autonomic distributed systems. It can be achieved by model-based management of dynamic architectures. Describing dynamic architectures includes defining rules for reconfiguration management. Within this research context, several works have been conducted using formal specification to handle this complexity. Graph and graph rewriting-based approaches showed, through many studies, their appropriateness to tackle architectural adaptation problems. However, scalability of such approaches remains an open issue and has been rarely explored. In this paper, we investigate this issue. We introduce a graph-based general approach for handling of dynamic architectures and we illustrate it within a scenario of collaboration support in crisis management systems. We elaborate the formal models for dynamic architecture management. Using the French Grid GRID5000, we conducted an experimental study to assess the scalability of the elaborated models.