MEDAL: An AI-Driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence

Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL, an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps)across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case

A Software-Agnostic Agent-based Platform for Modelling Emerging Mobility Systems

Due to the rapidly accelerated innovation cycle in transport and the emergence of new mobility concepts and technologies, public authorities, policy makers, and transport planners are currently in need of the tools for sustainable spatial and transport planning in the new mobility era. In this paper, a new modular, software-agnostic and activity-based spatial and transport planning platform is designed, i.e, the HARMONY Model Suite, that facilitates a novel integration of new and existing spatial and transport modelling tools. The paper focuses on describing the architecture of the platform and its passenger mobility simulation framework, which integrates -in an interoperable manner- activity-based models, mobility service management, and traffic simulation tools for evaluating new mobility system dynamics. The service management controllers for new mobility concepts are discussed in more detail with regards to their functionality and applicability

Decentralized Optimization of Vehicle Route Planning - A Cross-City Comparative Study

The introduction of connected and autonomous vehicles enables new possibilities in vehicle routing: Knowing the origin and destination of each vehicle in the network can allow for coordinated real-time routing of the vehicles to optimize network performance. However, this relies on individual vehicles being altruistic i.e., willing to accept alternative less-preferred routes. We conduct a study to compare different levels of agent altruism in decentralized vehicles coordination and the effect on the network-level traffic performance. This work introduces novel load-balancing scenarios of traffic flow in real-world cities for varied levels of agent altruism. We show evidence that the new decentralized optimization router is more effective with networks of high load

Open reduction and internal fixation compared to closed reduction and external fixation in distal radial fractures: A randomized study of 50 patients

Background and purpose In unstable distal radial fractures that are impossible to reduce or to maintain in reduced position, the treatment of choice is operation. The type of operation and the choice of implant, however, is a matter of discussion. Our aim was to investigate whether open reduction and internal fixation would produce a better result than traditional external fixation

Control Strategies for Self-Adaptive Software Systems

The pervasiveness and growing complexity of software systems are challenging software engineering to design systems that can adapt their behavior to withstand unpredictable, uncertain, and continuously changing execution environments. Control theoretical adaptation mechanisms have received growing interest from the software engineering community in the last few years for their mathematical grounding, allowing formal guarantees on the behavior of the controlled systems. However, most of these mechanisms are tailored to specific applications and can hardly be generalized into broadly applicable software design and development processes. This article discusses a reference control design process, from goal identification to the verification and validation of the controlled system. A taxonomy of the main control strategies is introduced, analyzing their applicability to software adaptation for both functional and nonfunctional goals. A brief extract on how to deal with uncertainty complements the discussion. Finally, the article highlights a set of open challenges, both for the software engineering and the control theory research communities

Repair of complete nerve lacerations at the forearm: An outcome study using Rosén-Lundborg protocol

A comparison of outcomes based on a scoring system for assessments, described by Rosén and Lundborg, after sharp complete laceration of median and/or ulnar nerves at various levels in the forearm was carried out. There were 66 males (90.4%) and 7 females (9.6%), with a mean age of 31 years (range: 14-62 years). The patients were categorized into three groups according to the type of nerve injury. The median nerve was injured in 25 cases (group M, 34.3%), the ulnar in 27 (group U, 36.9%), and both the nerves in 21 (group MU, 28.8%). The demographic data of the patients and the mechanism of injury were recorded. We also examined the employment status at the time of the injury and we estimated the percentage of patients who returned to their work after trauma. In all cases, a primary epineural repair was performed. Concomitant injuries were repaired in the same setting. The mean period of time between injury and surgery was 5.3 hours (range: 2-120 hours). A rehabilitation protocol and a reeducation program were followed in all cases. The mean follow-up was 3 years (range: 2-6 years), with more distal injuries having a shorter follow-up period. The total score was 2.71 in group M (range: 0.79-2.99) and 2.63 in group U (range: 0.63-3), with no significant differences observed. There was a significant difference between these two groups and group MU (total score 2.03, range: 0.49-2.76, P = 0.02). Up to the last follow-up, 61 patients (83.5%) had returned to their previous work. The Rosén-Lundborg model can be a useful and simple tool for the evaluation of the functional outcome after nerve injury and repair temporally reflecting the processes of regeneration and reinnervation. Copyright © 2010 Wiley-Liss, Inc

Automated Online Experiment-Driven Adaptation-Mechanics and Cost Aspects

© 2013 IEEE.As modern software-intensive systems become larger, more complex, and more customizable, it is desirable to optimize their functionality by runtime adaptations. However, in most cases it is infeasible to fully model and predict their behavior in advance, which is a classical requirement of runtime self-adaptation. To address this problem, we propose their self-adaptation based on a sequence of online experiments carried out in a production environment. The key idea is to evaluate each experiment by data analysis and determine the next potential experiment via an optimization strategy. The feasibility of the approach is illustrated on a use case devoted to online self-adaptation of traffic navigation where Bayesian optimization, grid search, and local search are employed as the optimization strategies. Furthermore, the cost of the experiments is discussed and three key cost components are examined-time cost, adaptation cost, and endurability cost

MEDAL: An AI-Driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence

© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL—an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps) across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case

Context-aware, Autonomous and Smart Architectures (CASA@ECSA 2017)

International audienceSoftware is becoming more and more aware of its execution context. Decisions made at design time are moved at run time to enhance the services offered by the software. The Context-aware, Autonomous, and Smart Architectures (CASA) workshop aims to address the issues and challenges raised by the development and evaluation of software that is context-aware, dynamic, autonomous, smart, adaptive, self-managed. Novel approaches are needed to face the new issues raised by such software. Further, existing architectural solutions should be adapted and improved to meet the dynamic requirements of today systems