2,590 research outputs found
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
PaPaS: A Portable, Lightweight, and Generic Framework for Parallel Parameter Studies
The current landscape of scientific research is widely based on modeling and
simulation, typically with complexity in the simulation's flow of execution and
parameterization properties. Execution flows are not necessarily
straightforward since they may need multiple processing tasks and iterations.
Furthermore, parameter and performance studies are common approaches used to
characterize a simulation, often requiring traversal of a large parameter
space. High-performance computers offer practical resources at the expense of
users handling the setup, submission, and management of jobs. This work
presents the design of PaPaS, a portable, lightweight, and generic workflow
framework for conducting parallel parameter and performance studies. Workflows
are defined using parameter files based on keyword-value pairs syntax, thus
removing from the user the overhead of creating complex scripts to manage the
workflow. A parameter set consists of any combination of environment variables,
files, partial file contents, and command line arguments. PaPaS is being
developed in Python 3 with support for distributed parallelization using SSH,
batch systems, and C++ MPI. The PaPaS framework will run as user processes, and
can be used in single/multi-node and multi-tenant computing systems. An example
simulation using the BehaviorSpace tool from NetLogo and a matrix multiply
using OpenMP are presented as parameter and performance studies, respectively.
The results demonstrate that the PaPaS framework offers a simple method for
defining and managing parameter studies, while increasing resource utilization.Comment: 8 pages, 6 figures, PEARC '18: Practice and Experience in Advanced
Research Computing, July 22--26, 2018, Pittsburgh, PA, US
Plataforma de serviços para monitorização da cadeia de valor do pescado
Traceability in the food value chain is a topic of interest due to the advantages it brings to both the consumers, producers and regulatory authorities. This thesis describes my contributions during the design and implementation of a microservice based middleware for the Portuguese fish value chain considering current practices in the industry and the requirements of the stakeholders involved in the project, with the goal of integrating all the traceability information available from each operator to provide customers with the full story of the products they purchase. During this project I assumed many roles such as development, operations and even some security allowing me to improve my skills in all these fields and experimenting with the latest cloud native technologies such as containers and with DevOps practices.A rastreabilidade na cadeia de valor alimentar Ă© um tema de interesse pelas vantagens que traz aos consumidores, produtores e autoridades reguladoras. Esta dissertação descreve as minhas contribuições durante a conceção e implementação de um middleware baseado em micro-serviços para a cadeia de valor do pescado portuguesa considerando as práticas atuais da indĂşstria e os requisitos das partes interessadas envolvidas no projeto, com o objetivo de integrar toda a informação de rastreabilidade disponĂvel de cada um dos operadores para fornecer aos clientes a histĂłria completa dos produtos que adquirem. Durante este projeto, assumi muitas funções, como desenvolvimento, operações e atĂ© mesmo alguma segurança, o que me permitiu melhorar as minhas capacidades em todos essas disciplinas e experimentar as mais recentes tecnologias nativas da nuvem, como contentores e práticas de DevOps.Mestrado em Engenharia Informátic
Don't Repeat Yourself: Seamless Execution and Analysis of Extensive Network Experiments
This paper presents MACI, the first bespoke framework for the management, the
scalable execution, and the interactive analysis of a large number of network
experiments. Driven by the desire to avoid repetitive implementation of just a
few scripts for the execution and analysis of experiments, MACI emerged as a
generic framework for network experiments that significantly increases
efficiency and ensures reproducibility. To this end, MACI incorporates and
integrates established simulators and analysis tools to foster rapid but
systematic network experiments.
We found MACI indispensable in all phases of the research and development
process of various communication systems, such as i) an extensive DASH video
streaming study, ii) the systematic development and improvement of Multipath
TCP schedulers, and iii) research on a distributed topology graph pattern
matching algorithm. With this work, we make MACI publicly available to the
research community to advance efficient and reproducible network experiments
From SpaceStat to CyberGIS: Twenty Years of Spatial Data Analysis Software
This essay assesses the evolution of the way in which spatial data analytical methods have been incorporated into software tools over the past two decades. It is part retrospective and prospective, going beyond a historical review to outline some ideas about important factors that drove the software development, such as methodological advances, the open source movement and the advent of the internet and cyberinfrastructure. The review highlights activities carried out by the author and his collaborators and uses SpaceStat, GeoDa, PySAL and recent spatial analytical web services developed at the ASU GeoDa Center as illustrative examples. It outlines a vision for a spatial econometrics workbench as an example of the incorporation of spatial analytical functionality in a cyberGIS.
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