funcX: A Federated Function Serving Fabric for Science

Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approaches must enable computation to be mobile, so that, for example, it can occur near data, be triggered by events (e.g., arrival of new data), be offloaded to specialized accelerators, or run remotely where resources are available. They also require new design approaches in which monolithic applications can be decomposed into smaller components, that may in turn be executed separately and on the most suitable resources. To address these needs we present funcX---a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. funcX's endpoint software can transform existing clouds, clusters, and supercomputers into function serving systems, while funcX's cloud-hosted service provides transparent, secure, and reliable function execution across a federated ecosystem of endpoints. We motivate the need for funcX with several scientific case studies, present our prototype design and implementation, show optimizations that deliver throughput in excess of 1 million functions per second, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than more than 130000 concurrent workers.Comment: Accepted to ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020). arXiv admin note: substantial text overlap with arXiv:1908.0490

Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487

Big Data in Critical Infrastructures Security Monitoring: Challenges and Opportunities

Critical Infrastructures (CIs), such as smart power grids, transport systems, and financial infrastructures, are more and more vulnerable to cyber threats, due to the adoption of commodity computing facilities. Despite the use of several monitoring tools, recent attacks have proven that current defensive mechanisms for CIs are not effective enough against most advanced threats. In this paper we explore the idea of a framework leveraging multiple data sources to improve protection capabilities of CIs. Challenges and opportunities are discussed along three main research directions: i) use of distinct and heterogeneous data sources, ii) monitoring with adaptive granularity, and iii) attack modeling and runtime combination of multiple data analysis techniques.Comment: EDCC-2014, BIG4CIP-201

Microstructures in subglacial and proglacial sediments : understanding faults, folds and fabrics, and the influence of water on the style of deformation

Macroscopic field and micromorphological studies have been carried out on subglacially and proglacially deformed glacigenic sequences at a number of sites throughout Scotland, UK. Examination of microstructures (folds, faults, hydrofractures, plasmic fabrics) aided understanding of the deformation histories preserved in the sediments, but a similar range of structures were developed in both subglacial and proglacial settings. Discrimination between subglacial and proglacial deformation was only possible when micromorphological data was used in conjunction with larger-scale field observations. Variations in lithology and water content were controlling factors influencing the style and apparent intensity of deformation recorded. Changes in pore-water content and pressure during deformation can lead to liquefaction and hydrofracturing, with early formed structures locally controlling the pattern of water-escape. Liquefaction can also lead to homogenisation of the sediments and the destruction of earlier deformation structures, even at relatively low strains. Beds or zones of liquefied sand and silt may form highly ‘lubricated’ detachments within the sediment pile, resulting in a marked reduction in the amount of shear transmitted to underlying units. A multidisciplinary approach, involving sedimentological, geomorphological, stratigraphical and structural field observations, combined with micromorphological analysis, is recommended to confidently unravel the glacitectonic history and depositional environment of most deformed glacigenic sedimentary sequences

Assessment of oxygen plasma ashing as a pre-treatment for radiocarbon dating

This study investigates the potential of low-temperature oxygen plasma ashing as a technique for decontaminating charcoal and wood samples prior to radiocarbon dating. Plasma ashing is demonstrated to be rapid, controllable and surface-specific, and clear differences are identified in the rate of ashing in different organic materials. However, the ability of plasma ashing to selectively remove these different components is limited in heterogeneous sample matrices. This is because oxidation is confined to the immediate sample surface. Comparison of radiocarbon dates obtained from identical aliquots of contaminated ancient charcoal pre-treated by acid-base-acid (ABA), acid-base-oxidation-stepped combustion (ABOx-SC) and plasma ashing suggests that the technique performs as well as the ABA pre-treatment but does not remove as much contamination as the ABOx-SC technique. Plasma-ashing may be particularly useful in cases where sample size is limiting