A Service Level Agreement Driven Framework to Customise Cloud Service Billing

Cloud service providers offer to their customers a variety of pricing policies, which range from the simple, yet widely used pay-as-you-go schema to complex discounted models. When executing the billing process, stakeholders have to consider usage metrics and service level objectives in order to obtain the correct billing and conform to the service level agreement in place. The more metrics, discount and compensations rules are added to the pricing schema, the more complex the billing generation results. In this paper we present a monitoring-based solution that enables the dynamically definition of both service level objectives and discount rules, so that providers can customise the billing generation process in terms of the service level agreement they offer. We validate our proposal in a real-world scenario, introducing a micro-service based software solution deployed in a Kubernetes cluster.Ministerio de Economía y Competitividad BELI (TIN2015-70560-R)Ministerio de Ciencia, Innovación y Universidades Horatio RTI2018-101204-B-C21Ministerio de Ciencia, Innovación y Universidades TIN2016-81978-REDTJunta de Andalucía P12-TIC-186

Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment

We present a desktop monitoring application that combines keyboard, mouse, desktop and application-level activities. It has been developed to discover differences in cognitive functioning amongst older computer users indicative of mild cognitive impairment (MCI). Following requirements capture from clinical domain experts, the tool collects all Microsoft Windows events deemed potentially useful for detecting early clinical indicators of dementia, with a view to further analysis to determine the most pertinent. Further requirements capture from potential end-users has resulted in a system that has little impact on users? daily activities and ensures data security from initial recording of events through to data analysis. We describe two experiments: firstly, volunteers were asked to perform a short set of known tasks; the second (ongoing) experiment is a longitudinal study, with the software currently successfully running on participants? computers

ASPIRO: Any-shot Structured Parsing-error-Induced ReprOmpting for Consistent Data-to-Text Generation

We present ASPIRO, an approach for structured data verbalisation into short template sentences in zero to few-shot settings. Unlike previous methods, our approach prompts large language models (LLMs) to directly produce entity-agnostic templates, rather than relying on LLMs to faithfully copy the given example entities, or validating/crafting the templates manually. We incorporate LLM re-prompting, triggered by algorithmic parsing checks, as well as the PARENT metric induced consistency validation to identify and rectify template generation problems in real-time. ASPIRO, compared to direct LLM output, averages 66\% parsing error rate reduction in generated verbalisations of RDF triples on the DART dataset. Our best 5-shot text-davinci-003 setup, scoring BLEU of 50.62, METEOR of 45.16, BLEURT of 0.82, NUBIA of 0.87, and PARENT of 0.8962 on the Rel2Text dataset, competes effectively with recent fine-tuned pre-trained language models.Comment: Accepted to Findings of EMNLP2023, code available at https://github.com/vejvarm/ASPIR

A Distributed Model for Stressors Monitoring Based on Environmental Smart Sensors

Nowadays, in many countries, stress is becoming a problem that increasingly affects the health of people. Suffering stress continuously can lead to serious behavioral disorders such as anxiety or depression. Every person, in his daily routine, can face many factors which can contribute to increase his stress level. This paper describes a flexible and distributed model to monitor environmental variables associated with stress, which provides adaptability to any environment in an agile way. This model was designed to transform stress environmental variables in value added information (key stress indicator) and to provide it to external systems, in both proactive and reactive mode. Thus, this value-added information will assist organizations and users in a personalized way helping in the detection and prevention of acute stress cases. Our proposed model is supported by an architecture that achieves the features above mentioned, in addition to interoperability, robustness, scalability, autonomy, efficient, low cost and consumption, and information availability in real time. Finally, a prototype of the system was implemented, allowing the validation of the proposal in different environments at the University of Alicante.This work has been granted by the Ministerio de Economía y Competitividad of the Spanish Government (Ref. TIN2014-53067-C3-1-R) and cofinanced by FEDER

The Problem of Semantics in the Metadata Mess

This presentation addresses problems related to the volume of available scientific data, and its accessibility or inaccessibility to researchers who seek it. Topics addressed include metadata and reducing semantic diversity, especially as they refer to geospatial and other architecture

Block-scoped access restriction technique for HTML content in web browsers

Web sites, web browsers, web site authors, web component authors, and end users interact in a complicated environment with many recognized and unrecognized trust relationships. The web browser is the arena in which many important trust relationships interact, thus it bears a considerable burden in protecting the interests and security of web end users as well as web site authors. Existing proposals, draft standards, implemented features, and web application techniques go a long way towards allowing rich and compelling content interactions, but they do not provide for rich, mutually-distrusting content to be safely embedded in a single page. This proposal suggests a declarative policy mechanism that permits untrusted content to be safely embedded in a web site while still retaining some richness. It also suggests a policy integration approach to allow multiple cooperative (but not necessarily trusting) parties to provide components of a policy that combine together in a safe manner. It incorporates techniques including fine-grained and coarse-grained permission dropping and white-listing protections for retained capabilities. Finally, the proposed concepts are applied to a number of real-world CVE vulnerabilities, and it is explained how the proposal does or does not prevent or mitigate the attack. The solution is shown to be effective against cross-style-scripting style attacks, and to not be effective at preventing incoming cross-site request forgery attacks

Smartlighting: a platform for intelligent building management

This work proposes a solution to endow buildings with efficiency and intelligence, exploiting the advantages of Complex Event Processing techniques and Internet of Things (IoT) principles. This combination allows efficient management of the entire infrastructure, an in particular enabling lighting to be tailored to the users needs. We validate this solution through a prototype implementation, based on wireless sensors and actuator networks that interact with the environment, using standard lightweight protocols designed for IoT. The prototype is based on high performance and real time platforms, and complex methods for analysis of large streams of data. The implementation is applied to a real world scenario, and will be used as the standard solution for management and automation of an existing building