Big-Data Streaming Applications Scheduling Based on Staged Multi-Armed Bandits

Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to adapt at run-time the throughput and resources allocated to the various streaming tasks depending on dynamically changing data stream characteristics and the desired applications performance (e.g., accuracy). However, most of state-of-the-art techniques consider only one single stream input in its application model input and assume that the system knows the amount of resources to allocate to each task to achieve a desired performance. To address these limitations, in this paper we propose a new systematic and efficient methodology and associated algorithms for online learning and energy-efficient scheduling of Big-Data streaming applications with multiple streams on many core systems with resource constraints. We formalize the problem of multi-stream scheduling as a staged decision problem in which the performance obtained for various resource allocations is unknown. The proposed scheduling methodology uses a novel class of online adaptive learning techniques which we refer to as staged multi-armed bandits (S-MAB). Our scheduler is able to learn online which processing method to assign to each stream and how to allocate its resources over time in order to maximize the performance on the fly, at run-time, without having access to any offline information. The proposed scheduler, applied on a face detection streaming application and without using any offline information, is able to achieve similar performance compared to an optimal semi-online solution that has full knowledge of the input stream where the differences in throughput, observed quality, resource usage and energy efficiency are less than 1, 0.3, 0.2 and 4 percent respectively. � 2016 IEEE

Methodologies synthesis

This deliverable deals with the modelling and analysis of interdependencies between critical infrastructures, focussing attention on two interdependent infrastructures studied in the context of CRUTIAL: the electric power infrastructure and the information infrastructures supporting management, control and maintenance functionality. The main objectives are: 1) investigate the main challenges to be addressed for the analysis and modelling of interdependencies, 2) review the modelling methodologies and tools that can be used to address these challenges and support the evaluation of the impact of interdependencies on the dependability and resilience of the service delivered to the users, and 3) present the preliminary directions investigated so far by the CRUTIAL consortium for describing and modelling interdependencies

Testing the robustness of controllers for self-adaptive systems

Self-Adaptive systems are software-intensive systems endowed with the ability to respond to a variety of changes that may occur in their environment, goals, or the system itself, by adapting their structure and behavior at run-time in an autonomous way. Controllers are complex components incorporated in self-adaptive systems, which are crucial to their function since they are in charge of adapting the target system by executing actions through effectors, based on information monitored by probes. However, although controllers are becoming critical in many application domains, so far very little has been done to assess their robustness. In this paper, we propose an approach for evaluating the robustness of controllers for self-adaptive software systems, aiming to identify faults in their design. Our proposal considers the stateful nature of the controller, and identifies a set of robustness tests, which includes the provision of mutated inputs to the interfaces between the controller and the target system (i.e., probes). The feasibility of the approach is evaluated on Rainbow, a framework for architecture-based self-adaptation, and in the context of the Znn.com case study

Resilient Computing Curriculum Draft -- ReSIST NoE Deliverable D16

This Deliverable presents the first version of ReSIST's Curriculum in Resilient Computing, limited to the description of the syllabi for the first year (Semesters 1 and 2) and indicates the line and title for the curriculum in the second year (semesters 3 and 4) and propose it to the general discussion for improvements. The curriculum will be updated and completed in successive versions that will take advantage of a large open discussion inside and outside ReSIS

Multi-level dependability modeling of interdependencies between the electricity and information infrastructures

The interdependencies between infrastructures may be the cause of serious problems in mission/safety critical systems. In the CRUTIAL project the interdependencies between the electricity infrastructure (EI) and the information infrastructure (II) responsible for its control, maintenance and management have been thoroughly studied; moreover countermeasures to substantially reduce the risk to interrupt the service have been developed in the project. The possible interdependencies have been investigated by means of model at different abstraction levels. In this paper, we present high level models describing the various interdependencies between the EI and the II infrastructures, then we illustrate on a simple scenario how these models can be detailed to allow the evaluation of some measures of dependability

Seismic Evaluation and Innovative Retrofit of a Historical Building in Tunisia

This paper summarizes work conducted within the framework of a European Commission funded project on the use of appropriate modern seismic protective systems in the conservation of Mediterranean historical buildings in earthquake-prone areas. The case study is the one-and-a-half-century-old Palace of Ksar Said, located near the Capital of Tunisia. At the center of the palace, a collection of portraits and furniture are preserved in a room of great architectural and historical value which is the most precious part of the building to be protected. Ambient vibration tests were conducted to measure the acceleration at selected locations of the building. Output-only modal identification techniques were applied to extract the modal signature of the structure. A finite element model of the palace was elaborated based on the measured characteristics of stone and mortar and updated according to its measured vibratory response. Seismic vulnerability assessment of the building was carried out via three-dimensional time-history dynamic analyses of the structure. Results indicate a high vulnerability that confirms the need for intervention. A retrofit scheme is proposed that consists of a steel frame directly, attached to the portrait room structure with added fluid viscous dampers. Vulnerability assessment of the retrofitted building reveals a substantial improvement especially in the vicinity of the portrait room. Copyright © 2004 John Wiley & Sons, Ltd

Genotype identification of Enterocytozoon bieneusi isolates from stool samples of HIV-infected Tunisian patients

The microsporidian species Enterocytozoon bieneusi is a major cause of chronic diarrhea and malabsorption in patients with AIDS. Genotyping was performed on seven E. bieneusi strains for the first time in Tunisia. All the strains were isolated from stool samples of humans with immunodeficiency virus (HIV) infection. Analysis of the ribosomal RNA gene internal transcribed spacer (rDNA ITS) allowed the identification of three distinct genotypes previously described in other studies. Genotypes D and B were characterized in four and two respectively. The Peruvian genotype (Peru 8) was detected in the last isolate. These results indicate a genetic diversity in E. bieneusi strains from HIV Tunisian patients and suggest the coexistence of both zoonotic and anthroponotic route of transmission

Genotype identification of

The microsporidian species Enterocytozoon bieneusi is a major cause of chronic diarrhea and malabsorption in patients with AIDS. Genotyping was performed on seven E. bieneusi strains for the first time in Tunisia. All the strains were isolated from stool samples of humans with immunodeficiency virus (HIV) infection. Analysis of the ribosomal RNA gene internal transcribed spacer (rDNA ITS) allowed the identification of three distinct genotypes previously described in other studies. Genotypes D and B were characterized in four and two respectively. The Peruvian genotype (Peru 8) was detected in the last isolate. These results indicate a genetic diversity in E. bieneusi strains from HIV Tunisian patients and suggest the coexistence of both zoonotic and anthroponotic route of transmission