NON-OPTIMIZED TEMPORAL STRUCTURES AS A FAILURE FACTOR IN VIRTUAL TEAMS

Despite the expected benefits of global virtual teams, their performance has been spotty and management continues to search for reasons why these teams fail. This work addresses this issue by performing a longitudinal case study of two virtual teams in order to uncover why one was more successful than the other. The study found that a key factor for one team’s poor performance was the entrainment of the temporal norms of both the countries and the social situations of the members that reduced the available real time meeting space to zero

Rational physical agent reasoning beyond logic

The paper addresses the problem of defining a theoretical physical agent framework that satisfies practical requirements of programmability by non-programmer engineers and at the same time permitting fast realtime operation of agents on digital computer networks. The objective of the new framework is to enable the satisfaction of performance requirements on autonomous vehicles and robots in space exploration, deep underwater exploration, defense reconnaissance, automated manufacturing and household automation

Swarm Relays: Distributed Self-Healing Ground-and-Air Connectivity Chains

The coordination of robot swarms - large decentralized teams of robots - generally relies on robust and efficient inter-robot communication. Maintaining communication between robots is particularly challenging in field deployments. Unstructured environments, limited computational resources, low bandwidth, and robot failures all contribute to the complexity of connectivity maintenance. In this paper, we propose a novel lightweight algorithm to navigate a group of robots in complex environments while maintaining connectivity by building a chain of robots. The algorithm is robust to single robot failures and can heal broken communication links. The algorithm works in 3D environments: when a region is unreachable by wheeled robots, the chain is extended with flying robots. We test the performance of the algorithm using up to 100 robots in a physics-based simulator with three mazes and different robot failure scenarios. We then validate the algorithm with physical platforms: 7 wheeled robots and 6 flying ones, in homogeneous and heterogeneous scenarios.Comment: 9 pages, 8 figures, Accepted for publication in Robotics and Automation Letters (RAL

INSPIRE Newsletter Spring 2021

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Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Optimization and Prediction Techniques for Self-Healing and Self-Learning Applications in a Trustworthy Cloud Continuum

The current IT market is more and more dominated by the “cloud continuum”. In the “traditional” cloud, computing resources are typically homogeneous in order to facilitate economies of scale. In contrast, in edge computing, computational resources are widely diverse, commonly with scarce capacities and must be managed very efficiently due to battery constraints or other limitations. A combination of resources and services at the edge (edge computing), in the core (cloud computing), and along the data path (fog computing) is needed through a trusted cloud continuum. This requires novel solutions for the creation, optimization, management, and automatic operation of such infrastructure through new approaches such as infrastructure as code (IaC). In this paper, we analyze how artificial intelligence (AI)-based techniques and tools can enhance the operation of complex applications to support the broad and multi-stage heterogeneity of the infrastructural layer in the “computing continuum” through the enhancement of IaC optimization, IaC self-learning, and IaC self-healing. To this extent, the presented work proposes a set of tools, methods, and techniques for applications’ operators to seamlessly select, combine, configure, and adapt computation resources all along the data path and support the complete service lifecycle covering: (1) optimized distributed application deployment over heterogeneous computing resources; (2) monitoring of execution platforms in real time including continuous control and trust of the infrastructural services; (3) application deployment and adaptation while optimizing the execution; and (4) application self-recovery to avoid compromising situations that may lead to an unexpected failure.This research was funded by the European project PIACERE (Horizon 2020 research and innovation Program, under grant agreement no 101000162)

Overcoming distance in virtual teams : effects of communication media, experience, and time pressure on distributed teamwork

Een virtueel team is een team waarvan de leden elkaar niet of zelden in levenden lijve ontmoeten, bijvoorbeeld omdat de teamleden verschillende werktijden hebben of op verschillende vestigingen van een organisatie werken. Anders dan reguliere teams zijn virtuele teams in grote mate afhankelijk van informatie- en communicatietechnologie. Een voorbeeld van een virtueel team is een ontwerpteam dat binnen een multinationaal bedrijf een nieuwe productlijn ontwikkelt vanaf verschillende locaties door gebruik te maken van e-mail en videovergaderingen. Een belangrijke bijdrage van het huidige onderzoek is dat het laat zien dat de beperkingen van gedistribueerd samenwerken die de wijdverbreide toepassing van virtuele teams hinderen, zijn te overkomen. Door een combinatie van relevante groupware en ervaring met samenwerken op afstand, kunnen virtuele teams werk produceren dat qua kwaliteit en hoeveelheid vergelijkbaar is met het werk van face-to-face teams. Het lijkt er dan ook op dat virtuele teams geen modeverschijnsel zijn. Virtuele teams zijn de toekomst