Mahdi Ben Alaya

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.

FRAMESELF: A Generic Context-Aware Autonomic Framework for Self-Management of Distributed Systems

The increasing complexity for the management of current distributed software and system needs new solutions. Designing autonomic systems which are self-managing and context aware is a solution and also a challenge. This paper proposes the FRAME SELF framework, a generic autonomic architecture based on context awareness and decision models built. The proposed solution capabilities are illustrated on the self-configuration of machine to machine networks (M2M). M2M needs to connect thousands of various fix and mobile machines that are widely distributed and evolve frequently according to their profile and context changes. FRAME SELF uses multi models representation based on ontologies and graphs to describe the M2M concepts and relationship on a multi-level knowledge base. Two communication patterns modules based on service-oriented and event-driven communications are dynamically selected and configured in deployment plans. A M2M smart metering use case is experimented to illustrate the proposed approach.

A Survey on M2M Service Networks

The number of industrial applications relying on the Machine to Machine (M2M) services exposed from physical world has been increasing in recent years. Such M2M services enable communication of devices with the core processes of companies. However, there is a big challenge related to complexity and to application-specific M2M systems called “vertical silos”. This paper focuses on reviewing the technologies of M2M service networks and discussing approaches from the perspectives of M2M information and services, M2M communication and M2M security. Finally, a discussion on technologies and approaches potentially enabling future autonomic M2M service networks are provided. According to our conclusions, it is seen that clear definition of the architectural principles is needed to solve the “vertical silo” problem and then, proceeding towards enabling autonomic capabilities for solving complexity problem appears feasible. Several areas of future research have been identified, e.g., autonomic information based services, optimization of communications with limited capability devices, real-time messaging, creation of trust and end to end security, adaptability, reliability, performance, interoperability, and maintenance.

AODA: an Autonomic and Ontology-Driven Architecture for service-oriented and event-driven systems

The large diversity and heterogeneity of collaborating objects and services in modern networking environments such as personal, vehicular or home networks makes difficult the efficient configuration, deployment and management of composite dynamic systems without a major participation of human actors. This paper proposes an autonomic architecture based on decision models built on ontologies and aimed at self-configuring and self-adapting information networks. Our work follows a top-down approach based on well-known and accepted standards. A detailed structure composite diagram is illustrated to describe AODA modules and show how they interact together. Our proposition had been implemented as an ecosystem-wide ontology aimed at characterising the properties of services and events related to consumers and producers entities participating in the information network. We propose a smart metering use case to compute the overload generated by our solution in handling a large number of objects.

AODA: An Autonomic and Ontology-Driven Architecture for Service-Oriented and Event-Driven Systems

The large diversity and heterogeneity of collaborating objects and services in modern networked environments such as personal, vehicular or home networks makes difficult the efficient configuration, deployment and management of composite dynamic systems without a major participation of human actors. This paper proposes an autonomic architecture based on decision models built on ontologies and aimed at self-configuring and self-adapting service-oriented and event-driven distributed systems. Our solution follows a top-down approach based on well-known and accepted standards and implemented as an ecosystem-wide ontology aimed at characterizing the properties of services and events related to consumers and producers entities participating in the autonomic collaborative environment.

Autonomic Energy-Aware Tasks Scheduling

The increasing processing capability of data-centers increases considerably their energy consumption which leads to important losses for companies. Energy-aware task scheduling is a new challenge to optimize the use of the computation power provided by multiple resources. In the context of Cloud resources usage depends on users requests which are generally unpredictable. Autonomic computing paradigm provides systems with self-managing capabilities helping to react to unstable situation. This article proposes an autonomic approach to provide energy-aware scheduling tasks. The generic autonomic computing framework FrameSelf coupled with the CloudSim energy-aware simulator is presented. The proposed solution enables to detect critical schedule situations and simulate new placements for tasks on DVFS enabled hosts in order to improve the global energy efficiency.

A Dynamic Random Graph Model for Diameter-Constrained Topologies in Networked Systems

Random graphs have been widely investigated in the literature because of their relevance to many scientific domains. In this brief, the attention is focused on diameter-constrained random graphs, which are useful in analyzing unstructured overlays for delay-bounded network applications and systems. To this end, a general process of arrivals is considered, which describes the sequence of vertex couples (i.e., node couples) among which a path composed of no more than D edges (i.e., links) has to be established. Accordingly, a topology formation mechanism M is formulated, expressing the rules that drive the addition of new edges, obeying to the constraint on the maximum diameter D. Third, using graph-theoretic arguments, an original discrete-time model is proposed, which describes the evolution of the average network degree (i.e., the average number of edges per node) subject to M and D. Fourth, the model is successfully validated using computer simulations in a wide range of scenarios (with up to 216 nodes). Finally, concrete examples are provided to illustrate useful applications of the proposed approach, also in the presence of link failures.

Semantic-Aware IoT Platforms

IoT paradigm applies to systems composed by numerous devices sharing information and making cooperative decisions with little or no human intervention. The IoT standard defined by oneM2M intiative furnishes a standardised framework for interoperable services that satisfies most of IoT modelling requirements. Prior standards and also oneM2M, while focusing on achieving interoperability at the communication level, do not achieve interoperability at the semantic level. In addition, the oneM2M standard does not address the issue of system adaptations to address system increasing complexity and evolving execution context. In this paper, the OM2M platform is presented as a solution for the interoperability challenge of IoT. An expressive ontology for IoT called IoT-O, making best use of already defined ontologies in specific domains such as sensor, observation, service, quantity kind, units, or time, is described to support semantic data. Finally, FRAMESELF framework is introduced to retrofit self-management capabilities into an IoT system.

Diameter-Constrained Overlays With Faulty Links: Equilibrium, Stability, and Upper Bounds

In network overlays, virtual links among remote processes are usually established to circumvent the limitations of underlying protocols. The resulting dynamics have been recently studied, based on a novel random graph model that assumes that no link failure can occur. In that model, the case of faulty links has been only marginally stated to stimulate future research activities. Unfortunately, network overlays are very prone to faulty links, which are caused by any possible reasons, that force a node to loose its connectivity. To bridge this gap, this brief deepens the implications of faulty links in diameter-constrained overlays and demonstrates the following: 1) the resulting system has a unique globally stable equilibrium point; 2) the number of links composing the network is upper bounded in closed form; and 3) the speed of convergence to the equilibrium point is upper bounded in closed form, too. These outcomes grant for a stable regime and serve for estimating the overhead incurred by network nodes and sizing them adequately. Finally, to characterize the application bounds of the model, a stochastic analysis of its accuracy has been proposed, along with an extensive simulation campaign that encompasses a wide range of scenarios.