International audience

The emission of CO2 due to ICT (Information and Communication Technologies) is found as equivalent to aviation sector. Although the energy consumption in ICT is due both to hardware and software. In recent decade, the energy efficiency studies focus on the hardware part, especially with the development of cloud computing. Indeed, it is the software application that is responsible for executing tasks, that indirectly affects the hardware energy consumption. This work focus on software energy consumption. We introduce a methodology which evaluates and improves the software greenability by considering its energy consumption, performance and readability. Contrary to existing methodologies, we associate the effect of several components (CPU, memory, disk and network) when estimating software energy consumption instead of considering only the CPU as it is the case in literature. Moreover, the proposed framework can dynamically examine source code to integrate some measurement functionality. A Tool to Estimate Energy Consumption (TEEC) is implemented and its applicability is demonstrated on the case of cloud-based business application provisioning software, called MADONA. MADONA allows dynamically generating service-oriented business applications by automatically composing business services and automatically deploying the generated applications on cloud environment.

With the increased popularity of cloud computing, the number and scales of cloud data centers have kept growing at unprecedented speeds. In the meanwhile, the energy consumption by the data centers has kept commensurately increasing as well. Therefore, the focus of cloud resource management and scheduling has relatively shifted from mere performance to also energy efficiency. In this paper, we present a novel, Energy-Aware Task Scheduling framework that makes integrated exploitation of the two well-known energy saving techniques, DVFS and VM Reuse, on cloud task scheduling in a data center. We present our scheduling approach and framework via a specific algorithm, called EATS-FFD, that assumes FFD as its base scheduling policy. With minor modification, the presented framework can be made to work with a different base scheduling policy, resulting in a correspondingly different scheduling algorithm. Our approach achieves better energy-efficiency without sacrificing system QoS. The effectiveness of our approach is evaluated under various experimental scenarios using the Cloud Report tool running on the open source CloudSim platform.

In this paper, we tackle privacy issues of data sharing services in a cloud environment. We propose a service- oriented privacy-preserving model for data integration across autonomous clouds. Our model allows to execute aggregations of cloud data sharing services without revealing any extra information to any of the involved services. Thus, involved services enforce locally their privacy policies by applying their own access control models and data anonymization algorithms. We illustrate lack of data protection in current data sources through examples of querying data in a healthcare system.

International audience

The paper presents an extension of solution plans generated by the graph-plan algorithm developed for AI planning. We post process the solution plans in order to generate executable workflows. We make the following main contributions: (i) we generate a Workflow Tree from the solution plans by encapsulating the actions into abstract workflow Blocks, (ii) we develop a methodology that uses the specification of workflow patterns in terms of Abstract State Machines in order to find the appropriate pattern to replace the abstract Block constructs in the workflow tree. (iii) We provide semi-automated support for agents in order to select the most specific pattern that fits their behavior at run-time. We have implemented the approach and our experiments with some real-world case studies show the viability of the proposed approach.

International audience

We propose a service-oriented privacy-preserving model for data integration across autonomous clouds. Our model allows to execute aggregations of cloud data sharing services without revealing any extra information to any of the involved services, i.e., none of involved services nor their providers are able to learn/infer any information about the data the other services provide beyond what these services already know.

The purpose of this paper is to define a generic methodology for semi automatic development of cloud-based business applications. This can be used by non-IT experts, such as business stakeholders, who trigger a business application development by simply stating its requirements in terms of business functionalities and constraints, QoS parameters, and her/his preferences. From these functionalities and constraints, Linked USDL requirements files are automatically generated. These files provide the basis for the cloud service discovery and launch the automatic development of cloud business applications. We present the first developments of our prototype.

We are motivated to study (and eventually deliver) a cloud facility that has its "back door" open for incorporating voluntary computing resources, and such implemented cloud infrastructures have the potential to harmoniously serve both on-demand and non on-demand requests/jobs at possibly the lowest cost because of involvement of the low or no cost of using voluntary computing resources. This short paper presents our idea of enhancing the "backfill computing" model originally proposed by Marshall, et al. by incorporating voluntary computing resources into the resource pools of clouds, and summarizes the simulation results we had recently obtained.

On-demand data integration is among the key challenges in Cloud Computing. In this paper, we present an ontology-based framework for describing and integrating data on the fly to answer transient business needs. We provide a semantic modeling for cloud's data services. The proposed modeling makes it possible to automatically resolve the different types of data heterogeneity that would arise when data from heterogeneous and autonomous providers need to be combined together to answer the business's data needs.

International audience

In this paper we enhance the mediation approach for interoperability in dynamic manufacturing networks (DMN) by decreasing the number of iterations that should be performed in order to find the right adaptation function between an expected message and the incoming ones. Then, we define a deployment architecture for mediators in dynamic collaboration environments that better handles the changes that could occur at run-time. We then conduct a set of experiments that demonstrate the efficiency of the introduced approach and architecture.

Nowadays, cloud applications are developed in Platforms as a Service and Infrastructures as a Service. Before the advent of Cloud computing, software engineering knew several approaches and methodologies for application development like: agiles methods and service oriented approaches. With cloud computing and the convergence toward "Everything as a Service", application development methods are moving to a new paradigm which abstracts the underlying architecture and infrastructure. We find in the literature, some work describing frameworks and architectures for cloud software development, but there is a lack of a methodology which covers the whole application development lifecycle. Furthermore, these work are mainly dedicated to developers. Our work fits into the perspective of defining a methodology for automatic cloud-based services-oriented business application development. The methodology we propose is designed for non-IT professional users. It avoids the huge technical background needed for cloud application development by automating the process of development, avoids PaaS dependency and advocates the implicit collaboration by reusing and composing services. We define a "requirements vocabulary", which is based on linked USDL principles and aims to describe the application requirements in a high level of abstraction of the development details.

Undeniably, cloud computing has been reshaping information technology drastically, and eventually making utility computing comes true. Internet services, ranging from simple word processing to online social networking, are progressively being shifted to the cloud. These services are interesting because they assure high scalability, availability, and reliability. Nevertheless, they are missing security as a vital non-functional requirement. As users no longer control their data and hand its governance over to cloud providers, data is significantly exposed to misuses and malicious attacks. In this article we present a lightweight software based agent that runs along with the cloud database on every host machine (i.e. virtual machine). The agents implement all the logic needed to prevent malicious attacks, monitor, and assess database transactions.

International audience

International audience

In a collaborative design environment, various software tools are utilized to enhance the product development. This entails a meaningful representation and exchange of product data semantics across these different systems. Semantic interoperability of product information refers to enabling the exchange of design intelligence, including construction history, parameters, features, and constraints. This is a crucial difference compared to current standards such as STEP that deliver "dumb" geometry, where no design intent is associated. To enable semantics data exchange, we propose an ontology-based approach, consisting in developing a "Common Design Features Ontology", called CDFO. Interoperability among ontologies is fulfilled by defining several mapping rules. We use a descriptive logic-based language, notably OWL DL to represent formally our ontology.

Currently, computer aided systems have concentrated on the capture and representation of geometric shape and technical information, as opposed to providing support for product design. The aim of this paper is to propose a framework for an integrated software that assists designers in the early design phases to work in co-operative and collaborative manner.

The concurrent design of a product and its manufacturing process requires a shared understanding of products and processes among many experts concerned with design and manufacturing. The objective of this paper is to provide an approach for the representation, integration and communication of different experts' viewpoints in the design and manufacturing phases. Firstly, we describe the problems related to concurrent design and current research works. Then we explain how, using the STEP standard, we can represent an integrated design and manufacturing model. As a case study, we consider the tracking of work-piece dimensions through all the different stages of product development, from design to machining. It is based on a model of machining tolerances based on a factory's machine-tool characterization. The chosen application case is a turning process. The model is validated by verification of the theoretical results in the case of machining several representative parts. Experiments point out the efficiency of our machining model. Finally, we present future developments of our integration work.