878 research outputs found
Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks
Sensors are present in various forms all around the world such as mobile
phones, surveillance cameras, smart televisions, intelligent refrigerators and
blood pressure monitors. Usually, most of the sensors are a part of some other
system with similar sensors that compose a network. One of such networks is
composed of millions of sensors connect to the Internet which is called
Internet of things (IoT). With the advances in wireless communication
technologies, multimedia sensors and their networks are expected to be major
components in IoT. Many studies have already been done on wireless multimedia
sensor networks in diverse domains like fire detection, city surveillance,
early warning systems, etc. All those applications position sensor nodes and
collect their data for a long time period with real-time data flow, which is
considered as big data. Big data may be structured or unstructured and needs to
be stored for further processing and analyzing. Analyzing multimedia big data
is a challenging task requiring a high-level modeling to efficiently extract
valuable information/knowledge from data. In this study, we propose a big
database model based on graph database model for handling data generated by
wireless multimedia sensor networks. We introduce a simulator to generate
synthetic data and store and query big data using graph model as a big
database. For this purpose, we evaluate the well-known graph-based NoSQL
databases, Neo4j and OrientDB, and a relational database, MySQL.We have run a
number of query experiments on our implemented simulator to show that which
database system(s) for surveillance in wireless multimedia sensor networks is
efficient and scalable
Creating a Relational Distributed Object Store
In and of itself, data storage has apparent business utility. But when we can
convert data to information, the utility of stored data increases dramatically.
It is the layering of relation atop the data mass that is the engine for such
conversion. Frank relation amongst discrete objects sporadically ingested is
rare, making the process of synthesizing such relation all the more
challenging, but the challenge must be met if we are ever to see an equivalent
business value for unstructured data as we already have with structured data.
This paper describes a novel construct, referred to as a relational distributed
object store (RDOS), that seeks to solve the twin problems of how to
persistently and reliably store petabytes of unstructured data while
simultaneously creating and persisting relations amongst billions of objects.Comment: 12 pages, 5 figure
Systems For Delivering Electric Vehicle Data Analytics
n the recent times, advances in scientific research related to electric vehicles led to generation of large amounts of data. This data is majorly logger data collected from various sensors in the vehicle. It is predominantly unstructured and non-relational in nature, also called Big Data. Analysis of such data needs a high performance information technology infrastructure that provides superior computational efficiency and storage capacity. It should be scalable to accommodate the growing data and ensure its security over a network. This research proposes an architecture built over Hadoop to effectively support distributed data management over a network for real-time data collection and storage, parallel processing, and faster random read access for information retrieval for decision-making.
Once imported into a database, the system can support efficient analysis and visualization of data as per user needs. These analytics can help understand correlations between data parameters under various circumstances. This system provides scalability to support data accumulation in the future and still perform analytics with less overhead. Overall, these open problems in EV data analytics are taken into consideration and a low-cost architecture for data management is researched
A software architecture for electro-mobility services: a milestone for sustainable remote vehicle capabilities
To face the tough competition, changing markets and technologies in automotive industry,
automakers have to be highly innovative. In the previous decades, innovations were
electronics and IT-driven, which increased exponentially the complexity of vehicle’s internal
network. Furthermore, the growing expectations and preferences of customers oblige these
manufacturers to adapt their business models and to also propose mobility-based services.
One other hand, there is also an increasing pressure from regulators to significantly reduce
the environmental footprint in transportation and mobility, down to zero in the foreseeable
future.
This dissertation investigates an architecture for communication and data exchange
within a complex and heterogeneous ecosystem. This communication takes place between
various third-party entities on one side, and between these entities and the infrastructure
on the other. The proposed solution reduces considerably the complexity of vehicle
communication and within the parties involved in the ODX life cycle. In such an
heterogeneous environment, a particular attention is paid to the protection of confidential
and private data. Confidential data here refers to the OEM’s know-how which is enclosed
in vehicle projects. The data delivered by a car during a vehicle communication session
might contain private data from customers. Our solution ensures that every entity of this
ecosystem has access only to data it has the right to. We designed our solution to be
non-technological-coupling so that it can be implemented in any platform to benefit from
the best environment suited for each task. We also proposed a data model for vehicle
projects, which improves query time during a vehicle diagnostic session. The scalability and
the backwards compatibility were also taken into account during the design phase of our
solution.
We proposed the necessary algorithms and the workflow to perform an efficient vehicle
diagnostic with considerably lower latency and substantially better complexity time and
space than current solutions. To prove the practicality of our design, we presented a
prototypical implementation of our design. Then, we analyzed the results of a series of tests
we performed on several vehicle models and projects. We also evaluated the prototype
against quality attributes in software engineering
Adaptive Mechanisms for Mobile Spatio-Temporal Applications
Mobile spatio-temporal applications play a key role in many mission critical fields, including Business Intelligence, Traffic Management and Disaster Management. They are characterized by high data volume, velocity and large and variable number of mobile users. The design and implementation of these applications should not only consider this variablility, but also support other quality requirements such as performance and cost. In this thesis we propose an architecture for mobile spatio-temporal applications, which enables multiple angles of adaptivity. We also introduce a two-level adaptation mechanism that ensures system performance while facilitating scalability and context-aware adaptivity. We validate the architecture and adaptation mechanisms by implementing a road quality assessment mobile application as a use case and by performing a series of experiments on cloud environment. We show that our proposed architecture can adapt at runtime and maintain service level objectives while offering cost-efficiency and robustness
ICSEA 2021: the sixteenth international conference on software engineering advances
The Sixteenth International Conference on Software Engineering Advances (ICSEA 2021), held on October 3 - 7, 2021 in Barcelona, Spain, continued a series of events covering a broad spectrum of software-related topics.
The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. The tracks treated the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learnt. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education.
The conference had the following tracks:
Advances in fundamentals for software development
Advanced mechanisms for software development
Advanced design tools for developing software
Software engineering for service computing (SOA and Cloud)
Advanced facilities for accessing software
Software performance
Software security, privacy, safeness
Advances in software testing
Specialized software advanced applications
Web Accessibility
Open source software
Agile and Lean approaches in software engineering
Software deployment and maintenance
Software engineering techniques, metrics, and formalisms
Software economics, adoption, and education
Business technology
Improving productivity in research on software engineering
Trends and achievements
Similar to the previous edition, this event continued to be very competitive in its selection process and very well perceived by the international software engineering community. As such, it is attracting excellent contributions and active participation from all over the world. We were very pleased to receive a large amount of top quality contributions.
We take here the opportunity to warmly thank all the members of the ICSEA 2021 technical program committee as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors that dedicated much of their time and efforts to contribute to the ICSEA 2021. We truly believe that thanks to all these efforts, the final conference program consists of top quality contributions.
This event could also not have been a reality without the support of many individuals, organizations and sponsors. We also gratefully thank the members of the ICSEA 2021 organizing committee for their help in handling the logistics and for their work that is making this professional meeting a success.
We hope the ICSEA 2021 was a successful international forum for the exchange of ideas and results between academia and industry and to promote further progress in software engineering research
Industrial Applications: New Solutions for the New Era
This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section
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