5,071 research outputs found
Microservices and serverless functions – lifecycle, performance, and resource utilisation of edge based real-time IoT analytics
Edge Computing harnesses resources close to the data sources to reduce end-to-end latency and allow real-time process automation for verticals such as Smart City, Healthcare and Industry 4.0. Edge resources are limited when compared to traditional Cloud data centres; hence the choice of proper resource management strategies in this context becomes paramount. Microservice and Function as a Service architectures support modular and agile patterns, compared to a monolithic design, through lightweight containerisation, continuous integration / deployment and scaling. The advantages brought about by these technologies may initially seem obvious, but we argue that their usage at the Edge deserves a more in-depth evaluation. By analysing both the software development and deployment lifecycle, along with performance and resource utilisation, this paper explores microservices and two alternative types of serverless functions to build edge real-time IoT analytics. In the experiments comparing these technologies, microservices generally exhibit slightly better end-to-end processing latency and resource utilisation than serverless functions. One of the serverless functions and the microservices excel at handling larger data streams with auto-scaling. Whilst serverless functions natively offer this feature, the choice of container orchestration framework may determine its availability for microservices. The other serverless function, while supporting a simpler lifecycle, is more suitable for low-invocation scenarios and faces challenges with parallel requests and inherent overhead, making it less suitable for real-time processing in demanding IoT settings
Safe passage for attachment systems:Can attachment security at international schools be measured, and is it at risk?
Relocations challenge attachment networks. Regardless of whether a person moves or is moved away from, relocation produces separation and loss. When such losses are repeatedly experienced without being adequately processed, a defensive shutting down of the attachment system could result, particularly when such experiences occur during or across the developmental years. At schools with substantial turnover, this possibility could be shaping youth in ways that compromise attachment security and young people’s willingness or ability to develop and maintain deep long-term relationships. Given the well-documented associations between attachment security, social support, and long-term physical and mental health, the hypothesis that mobility could erode attachment and relational health warrants exploration. International schools are logical settings to test such a hypothesis, given their frequently high turnover without confounding factors (e.g. war trauma or refugee experiences). In addition, repeated experiences of separation and loss in international school settings would seem likely to create mental associations for the young people involved regarding how they and others tend to respond to such situations in such settings, raising the possibility that people at such schools, or even the school itself, could collectively be represented as an attachment figure. Questions like these have received scant attention in the literature. They warrant consideration because of their potential to shape young people’s most general convictions regarding attachment, which could, in turn, have implications for young people’s ability to experience meaning in their lives
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses
In the vehicular mixed reality (MR) Metaverse, the distance between physical
and virtual entities can be overcome by fusing the physical and virtual
environments with multi-dimensional communications in autonomous driving
systems. Assisted by digital twin (DT) technologies, connected autonomous
vehicles (AVs), roadside units (RSU), and virtual simulators can maintain the
vehicular MR Metaverse via digital simulations for sharing data and making
driving decisions collaboratively. However, large-scale traffic and driving
simulation via realistic data collection and fusion from the physical world for
online prediction and offline training in autonomous driving systems are
difficult and costly. In this paper, we propose an autonomous driving
architecture, where generative AI is leveraged to synthesize unlimited
conditioned traffic and driving data in simulations for improving driving
safety and traffic efficiency. First, we propose a multi-task DT offloading
model for the reliable execution of heterogeneous DT tasks with different
requirements at RSUs. Then, based on the preferences of AV's DTs and collected
realistic data, virtual simulators can synthesize unlimited conditioned driving
and traffic datasets to further improve robustness. Finally, we propose a
multi-task enhanced auction-based mechanism to provide fine-grained incentives
for RSUs in providing resources for autonomous driving. The property analysis
and experimental results demonstrate that the proposed mechanism and
architecture are strategy-proof and effective, respectively
Discussion on drivers and proposition of approaches to support the transition of traditional electricity consumers to prosumers
In recent years, traditional power systems have undergone a significant transition, mainly
related to the massive penetration of Renewable Energy Sources (RES). More specifically, the
transformation of residential consumers into prosumers has been challenging to the traditional
operation of electricity markets. This transition brings new challenges and opportunities to
the power system, leading to new Business Model (BM). One widely discussed change is
related to a consumer-centric or prosumer-driven approach, promoting increased participation
of small consumers in power systems. The present thesis aims at discussing the recent BMs as
enablers of the increasing prosumers’ role in the energy market and power system worldwide,
deepening the discussion with a holistic view of the Brazilian context. To do so, it defines
the main features of prosumers and their general related regulation as well as possible market
designs within power systems. Moreover, the work intends to contribute to the knowledge,
identification and understanding of the main regulatory barriers and enablers for the development
of those BMs in the Brazilian energy market. In addition, it discusses enabling technologies to
properly create the conditions that sustain new prosumer-driven markets. Then, it presents a
comprehensive review of existing and innovative BMs and a discussion on their future roles in
modern power systems and, in the Brazilian regulatory framework seeking to guide the decisions
for the country to develop its political and regulatory environment in the future. Moreover, a
set of recommendations for promoting these BMs in the power system worldwide is provided
along with policy recommendations to promote prosumers aggregation in the Brazilian energy
sector. An important conclusion is that, even though economically possible, not all innovative
BMs can spread around the world due to regulatory issues. Seeking to further explore one of
the prosumer-driven approaches presented and the challenges imposed by this innovative BM,
a study of energy and reserve markets based on the Peer-to-Peer (P2P) structure is carried out.
This structure is very promising for the prosumers’ promotion but presents some challenges for
the network operation. A critical challenge is to ensure that network constraints are not violated
due to energy trades between peers and neither due to the use of reserve capacity. Therefore,
two methodologies are proposed. First, is proposed a three-step approach (P2PTDF), using
Topological Distribution Factors (TDF) to penalize peers responsible for violations that may
occur in the network constraints, ensuring a feasible solution. Second, it is proposed a new
integrated prosumers-DSO approach applied in P2P energy and reserve tradings that also ensures
the feasibility of both energy and reserve transactions under network constraints. The proposed
approach includes the estimation of reserve requirements based on the RES uncertain behavior
from historical generation data, which allows identifying RES patterns. The proposed models
are assessed through a case study that uses a 14-bus system, under the technical and economic
criteria. The results show that the approaches can ensure a feasible network operation.Nos últimos anos, os sistemas tradicionais de energia passaram por uma transição significativa, principalmente relacionada à penetração massiva de fontes de energia renováveis (do
inglês, Renewable energy sources-RES). Mais especificamente, a transformação de consumidores
residenciais em prosumidores tem desafiado a atual operação do mercado de energia elétrica.
Essa transição traz novos desafios e oportunidades para o sistema elétrico, levando a novos
modelos de negócios (do inglês, Business Models-BM). Uma mudança amplamente discutida
está relacionada a uma abordagem centrada no consumidor ou direcionada ao prossumidor,
promovendo maior participação de pequenos consumidores nos sistemas de energia. A presente
tese tem como objetivo discutir os recentes BMs como facilitadores do crescente papel dos
prosumidores no mercado de energia e no sistema elétrico mundial, aprofundando a discussão
com uma visão holística do contexto brasileiro. Para tanto, define as principais características
dos prosumidores e sua regulamentação geral relacionada, bem como possíveis designs de
mercado dentro dos sistemas de energia. Além disso, o trabalho pretende contribuir para o
conhecimento, identificação e compreensão das principais barreiras regulatórias e facilitadoras
para o desenvolvimento desses BMs no mercado brasileiro de energia. Assim como, discutir as
tecnologias importantes para criar adequadamente as condições que sustentam novos mercados
orientados ao consumidor final. Em seguida, apresenta uma revisão abrangente dos BMs existentes e inovadores e uma discussão sobre seus papéis futuros nos sistemas de energia modernos
e, no quadro regulatório brasileiro, buscando orientar as decisões para que o país desenvolva
seu ambiente político e regulatório no futuro. Além disso, um conjunto de recomendações
para promover esses BMs no sistema de energia em todo o mundo é fornecido juntamente com
recomendações de políticas para promover a agregação de prosumidores no setor de energia
brasileiro. Uma conclusão importante é que, mesmo sendo economicamente possível, nem todos
os BMs inovadores podem se espalhar pelo mundo devido a obstáculos regulatórias. Buscando
explorar ainda mais uma das abordagens orientadas ao prosumidor apresentadas e os desafios
impostos por este BM inovador, é realizado um estudo dos mercados de energia e de reserva com
base na estrutura ponto a ponto (do inglês, peer-to-peer-P2P). Esta estrutura é muito promissora
para a promoção dos prosumidores mas apresenta alguns desafios para o funcionamento da rede.
Um desafio crítico é garantir que as restrições da rede não sejam violadas devido a negociações
de energia entre pares e nem devido ao uso da capacidade de reserva. Portanto, duas metodologias são propostas. Primeiramente, é proposta uma abordagem em três passos (P2PTDF),
utilizando Fatores de Distribuição Topológica (do inglês, Topological Distribution Factors-TDF
) para penalizar os peers responsáveis por violações que possam ocorrer nas restrições da rede,
garantindo uma solução viável. Em segundo lugar, é proposta uma nova abordagem integrada
de prosumidores-DSO aplicada em transações P2P de energia e reserva que também garante a
viabilidade de transações de energia e reserva sob restrições de rede. A abordagem proposta
inclui a estimativa dos requisitos de reserva com base no comportamento incerto da RES a partir
de dados históricos de geração, o que permite identificar padrões de RES. Os modelos propostos
são avaliados através de um estudo de caso que utiliza um sistema de 14 barras, sob os critérios
técnico e econômico. Os resultados mostram que as abordagens podem garantir uma operação
de rede viável abrangendo energia e mercados de reserva
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A hybrid many-objective optimization algorithm for task offloading and resource allocation in multi-server mobile edge computing networks
Mobile edge computing (MEC) is an effective computing tool to cope with the explosive growth of data traffic. It plays a vital role in improving the quality of service for user task computing. However, the existing solutions rarely address all the significant factors that impact the quality of service. To challenge this problem, a trusted many-objective model is built by comprehensively considering the task time delay, server energy consumption, trust metrics between task and server, and user experience utility factors in multi-server MEC networks. We decompose the original problem into task offloading (TO) and resource allocation (RA) to address the model. Then a novel hybrid many-objective optimization algorithm based on cascading clustering and incremental learning is designed to optimize the TO decision solutions. A low-complexity heuristic method is adopted based on the optimal TO decision solutions to optimize the RA problem continuously. To verify the model’s validity and the optimisation algorithm’s superiority, five other advanced many-objective algorithms are used for comparison. The results show that our algorithm has more than half the number of the superior values for the benchmark problem. The obtained model solution shows good performance on different indicators metrics for the decomposition problem
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