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Data management applications deployed on IaaS cloud environments must simultaneously strive to minimize cost and provide good performance. Balancing these two goals requires complex decision-making across a number of axes: resource provisioning, query placement, and query scheduling. While previous works have addressed each axis in isolation for specific types of performance goals, this demonstration...
We present a novel approach for detecting malicious user activity in databases. Specifically, we propose a new machine learning algorithm for detecting attacks such as a stolen user account or illegal use by a user. Our algorithm relies on two main components that examine the consistency of a user's activity and compare it with activity patterns learned from past access. The first component tests...
Mobile app testing and evaluation requires exposing the app to a wide array of real world context conditions viz. location, sensor values, network conditions etc. Such comprehensive context conditions are difficult to create in a development environment on a real device, therefore, simulating them in a mobile emulator is a promising alternative. We present ContextMonkey, a framework for context generation...
This paper explores scalable implementation strategies for carrying out lazy schema evolution in NoSQL data stores. For decades, schema evolution has been an evergreen in database research. Yet new challenges arise in the context of cloud-hosted data backends: With all database reads and writes charged by the provider, migrating the entire data instance eagerly into a new schema can be prohibitively...
The modern infrastructure of electric grid known as smart grid is based on advanced communication and information technologies. The concept of data integration between heterogeneous data sources of smart grid reveals some challenges. The focus of this paper is on data integration as one of the major challenges in IT infrastructure of smart grid. In this paper, a semantic-based hierarchical integration...
Filtering and finding items of interest in large volumes of data, such as products in an e-commerce application or invoices in an ERP web platform can be a burdensome task, either for novice users that do not have insights on how the data is modeled or for those users who are already accustomed to the used system, but usually their filtering needs are significantly more complex. Natural language processing...
Smart homes have gained attraction for several years in people's daily lives and are still increasing. They provide a fruitful foundation for the creation of social network services as they escort habits and regular activities of people at home, along their way or even at work. Smart homes and their current development stage are not only able to support people by intelligent functionality but also...
Mining frequent patterns is a crucial task in data mining. Most of the existing frequent pattern mining methods find the complete set of frequent patterns from a given dataset. However, in real-life scenarios we often need to predict the future frequent patterns for different tasks such as business policy making, web page recommendation, stock-market behavior and road traffic analysis. Predicting...
In the context of large engineering projects the effective and efficient exchange and versioning of information from different engineering disciplines is essential. Semantic data integration approaches provide the necessary means to overcome the gap between heterogeneous local engineering tool concepts and common project-level concepts which enable the mapping of engineering data coming from different...
Big Data Era brings two main dimensions, which are heterogeneity and contextual data. The heterogeneity may occur at syntax and semantic levels. Ontologies are largely used to reduce these heterogeneities. Data has limited value if not paired with its context. Usually the internal data of companies are not connected to the rest of data universe including news, weather, user profiles, etc. In Engineering...
Change data capture (CDC) is an approach to data integration that is used to determine and track the data that has changed so that action can be taken using the change data. However, the state of art of change data capture (CDC) in the context of document-oriented NoSQL databases is not mature. Therefore, it is urgent to require a NoSQL CDC solution. Although some manufacturers of NoSQL databases...
The "Internet of Things" (IoT) represents an em- bodiment of the continuous convergence between the physical facet of human activities and its reflection on the informa- tion world. In the context of “Industrial Internet”, where the operation of complex physical machinery is integrated with networked sensors and software applications, IoT is under- stood as a technological enabler of significant...
Nowadays Big Data becomes one of the biggest buzz concepts in IT world especially with the vertiginous development driving the increase of data encouraged by the emergence of high technologies of storage like cloud computing. Big Data can create efficient challenging solutions in health, security, government and more; and usher in a new era of analytics and decisions. Knowledge Management comprises...
Data is of great importance in computer science and in particular in information systems and how data is treated has major impact on a system's quality attributes. Nevertheless, software architecture research, literature, and practice often neglect data and focus instead on other architectural topics like components and connectors or the management of architecture decisions in general. This paper...
This paper proposes a data model for the management of information exchanged during trust negotiation. The information exchanged during trust negotiation has been considered to be structured or may be converted to a structured format Uncertainty associated with such information transfer has been modeled as probabilistic data Updating of message has been explained using a particular application domain...
In order to easily query and blend structured data on the web a query formulation language is presented. The core novelty of this is that it permits people with restricted IT skills to explore and query one (or multiple) data sources without prior knowledge about the schema, structure, terminology, or any technological details of these sources. Data source considered may be either an offline or inline...
IoT/Bigdata is a hot research topic all over the world in recent years and is expecting to change the world greatly in the near future. Comparing with the data in traditional websites, Bigdata from IoT devices have 4 big V-features, i.e., volume, velocity, variety, and veracity. Due to the above four features, it is hard to provide timely services to users by data analysis, especially with the great...
NoSQL databases opt not to offer important abstractions traditionally found in relational databases in order to achieve high levels of scalability and availability: transactional guarantees and strong data consistency. In this work we propose pH1, a generic middleware layer over NoSQL databases that offers transactional guarantees with Snapshot Isolation. This is achieved in a non-intrusive manner,...
Over time, data warehouse (DW) schema and instances may undergo several changes reflecting the changes that occur in data sources or the emergence of new user analysis requirements. To deal with these changes and ensure the persistence of historical states of DW, we propose a multiversion DW model that ensures the temporal versioning of DW schema components as well as of its instances. Our model supports...
Cloud computing has recently emerged as a new computing paradigm enabling on-demand and scalable provision of resources, platforms and software as services. In order to satisfy different storage requirements, cloud applications usually need to access and interact with different relational and NoSQL data stores having heterogeneous APIs. This APIs heterogeneity induces two main problems. First it ties...
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