The ENTICE Approach to Decompose Monolithic Services into Microservices

Cloud computing has enabled elastic and on-demand service provisioning to achieve more efficient resource utilisation and quicker responses to varying application loads. Virtual machines, the building blocks of clouds, can be created using provider specific templates stored in proprietary repositories, which may lead to provider lock-in and decreased portability. Despite these enabling technologies, large scale service oriented applications are still mostly inelastic. Such applications often use monolithic services that limit the elasticity (e.g., by obstructing the replicability of parts of a monolithic service). Decomposing these services (leading to smaller, more targeted and more modular services) would open towards elasticity, but the decomposition process is mostly manual. This paper introduces a methodology for decomposing monolithic services to several so called microservices. The proposed methodology applies several outcomes of the ENTICE project (namely its image synthesis and optimisation tools). Finally, the paper provides insights on how these outcomes help revitalise past monolithic services, and what techniques are applied to aid future microservice developers

Strategies for Increased Energy Awareness in Cloud Federations

This chapter first identifies three scenarios that current energy aware cloud solutions cannot handle as isolated IaaS, but their federative efforts offer opportunities to be explored. These scenarios are centered around: (i) multi-datacenter cloud operator, (ii) commercial cloud federations, (iii) academic cloud federations. Based on these scenarios, we identify energy-aware scheduling policies to be applied in the management solutions of cloud federations. Among others, these policies should consider the behavior of independent administrative domains, the frequently contradicting goals of the participating clouds and federation wide energy consumption

Investigation of drug distribution in tablets using surface enhanced Raman chemical imaging

This paper reports the first application of surface enhanced Raman chemical imaging on pharmaceutical tablets containing the active ingredient (API) in very low concentrations.Taking advantage of the extremely intensive Raman signals in the presence of silver colloids,image aquisition time was radically decreased. Moreover, the investigation of drug distribution below the detection limit of regular micro-Raman spectrometry was made feasible. The characteristics of different manufacturing technologies could be revealed at very low API concentrations by using chemometric methods for processing and evaluating the large number of varying spectra provided with this imaging method

Quantitative Evaluation of Drug Distribution in Tablets of Various Structures via Raman Mapping

Hyperspectral imaging was applied to provide quantitative spatial information about pharmaceutical samples. The aim was to characterize the distribution of active pharmaceutical ingredient (API) in manufactured samples quantitatively. Two kind of API, imipramine and spironolactone were applied in three conventional and two continuous processing technologies. The homogeneity of distributions of 10% API was determined through Raman maps applying macropixel analysis method. Non-overlapping macropixel analysis (Poole-index) and calculation of distributional homogeneity indices (DHIs) were compared as a measure of homogeneity. Non-overlapping macropixel approach proved to be more sensible than DHI evaluation. For enhancing efficacy of DHI we suggest a correction by weighting scores and considering relative standard deviations. This way the capability of DHI can be improved significantly. The very slight differences between the continuous methods (the homogeneity of which are much higher than that of conventional technologies) could be quantified

Flax fibre reinforced PLA/TPS biocomposites flame retarded with multifunctional additive system

Fully biodegradable composites were developed, possessing prominent mechanical performance and reduced flammability at the same time. The manufactured composites consisted of PLA/TPS biopolymer matrices reinforced with chopped flax fibres. The flammability of the prepared biocomposites was reduced by a newly synthesized multifunctional additive system. Glycerol phosphate (GP), a plasticizer of starch with flame retardant potential, and a novel phosphorous-silane (PSil), applied as a surface treating agent of the reinforcing biofibres, were successfully combined in order to reduce the flammability of the prepared biocomposites. Owing to the beneficial effect of the applied multifunctional additive system, a loading of as low as 10 wt% of ammonium polyphosphate (APP) proved to be sufficient to provide prominent levels of flame retardancy to the composites, i.e. V-0 rating according to UL94, 33 vol% LOI and a 40% reduction of heat emission were achieved. Furthermore, the combined application of the surface treated reinforcing flax fibres and plasticizer in the biodegradable, flame retarded biocomposites resulted in well-balanced strength and stiffness

Orchestrated Platform for Cyber-Physical Systems

One of the main driving forces in the era of cyber-physical systems (CPSs) is the introduction of massive sensor networks (or nowadays various Internet of things solutions as well) into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data have to be ingested at the server side in order to generate and make the "twin digital model" or virtual factory of the existing physical processes for (among others) predictive simulation and scheduling purposes usable. In this paper, we focus on our ultimate goal, a novel software container-based approach with cloud agnostic orchestration facilities that enable the system operators in the industry to create and manage scalable, virtual IT platforms on-demand for these two typical major pillars of CPS: (1) server-side (i.e., back-end) framework for sensor networks and (2) configurable simulation tool for predicting the behavior of manufacturing systems. The paper discusses the scalability of the applied discrete-event simulation tool and the layered back-end framework starting from simple virtual machine-level to sophisticated multilevel autoscaling use case scenario. The presented achievements and evaluations leverage on (among others) the synergy of the existing EasySim simulator, our new CQueue software container manager, the continuously developed Octopus cloud orchestrator tool, and the latest version of the evolving MiCADO framework for integrating such tools into a unified platform