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In computer science, contextualization is the process of identifying the data relevant to an entity (e.g., a person or a city) based on the entity's contextual information. [1]
Context or contextual information is any information about any entity that can be used to effectively reduce the amount of reasoning required (via filtering, aggregation, and inference) for decision making within the scope of a specific application. [2] Contextualisation is then the process of identifying the data relevant to an entity based on the entity's contextual information. Contextualisation excludes irrelevant data from consideration and has the potential to reduce data from several aspects including volume, velocity, and variety in large-scale data intensive applications (Yavari et al.). [2] [1]
The main usage of "contextualisation" is in improving the process of data:
In telecommunication, provisioning involves the process of preparing and equipping a network to allow it to provide new services to its users. In National Security/Emergency Preparedness telecommunications services, "provisioning" equates to "initiation" and includes altering the state of an existing priority service or capability.
Context awareness is a property of mobile devices that is defined complementarily to location awareness. Whereas location may determine how certain processes around a contributing device operate, context may be applied more flexibly with mobile users, especially with users of smart phones. Context awareness originated as a term from ubiquitous computing or as so-called pervasive computing which sought to deal with linking changes in the environment with computer systems, which are otherwise static. The term has also been applied to business theory in relation to contextual application design and business process management issues.
Embedded software is computer software, written to control machines or devices that are not typically thought of as computers, commonly known as embedded systems. It is typically specialized for the particular hardware that it runs on and has time and memory constraints. This term is sometimes used interchangeably with firmware.
Mahadev Satyanarayanan (Satya) is an experimental computer scientist, an ACM and IEEE fellow, and the Carnegie Group Professor of Computer Science at Carnegie Mellon University (CMU).
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.
The Internet of things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet.
The IEEE Communications Society (ComSoc) promotes the advancement of science, technology and applications in communications and related disciplines. It fosters presentation and exchange of information among its members and the technical community throughout the world. The Society maintains a high standard of professionalism and technical competency. The IEEE Communications Society is a professional society of the IEEE.
Amit Sheth is a computer scientist at University of South Carolina in Columbia, South Carolina. He is the founding Director of the Artificial Intelligence Institute, and a Professor of Computer Science and Engineering. From 2007 to June 2019, he was the Lexis Nexis Ohio Eminent Scholar, director of the Ohio Center of Excellence in Knowledge-enabled Computing, and a Professor of Computer Science at Wright State University. Sheth's work has been cited by over 48,800 publications. He has an h-index of 106, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.
Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. The term is generally used to describe data centers available to many users over the Internet. Large clouds, predominant today, often have functions distributed over multiple locations from central servers. If the connection to the user is relatively close, it may be designated an edge server.
In computing, data as a service, or DaaS, is enabled by software as a service (SaaS). Like all "as a service" (aaS) technology, DaaS builds on the concept that its data product can be provided to the user on demand, regardless of geographic or organizational separation between provider and consumer. Service-oriented architecture (SOA), and the widespread use of API, has rendered the platform on which the data resides as irrelevant.
Mobile Cloud Computing (MCC) is the combination of cloud computing and mobile computing to bring rich computational resources to mobile users, network operators, as well as cloud computing providers. The ultimate goal of MCC is to enable execution of rich mobile applications on a plethora of mobile devices, with a rich user experience. MCC provides business opportunities for mobile network operators as well as cloud providers. More comprehensively, MCC can be defined as "a rich mobile computing technology that leverages unified elastic resources of varied clouds and network technologies toward unrestricted functionality, storage, and mobility to serve a multitude of mobile devices anywhere, anytime through the channel of Ethernet or Internet regardless of heterogeneous environments and platforms based on the pay-as-you-use principle."
Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes or petabytes in size and typically referred to as big data. Computing applications which devote most of their execution time to computational requirements are deemed compute-intensive, whereas computing applications which require large volumes of data and devote most of their processing time to I/O and manipulation of data are deemed data-intensive.
SQLstream is a distributed, SQL standards-compliant plus Java stream processing platform. SQLstream, Inc. is based in San Francisco, California and was launched in 2009 by Damian Black, Edan Kabatchnik and Julian Hyde, author of the open source Mondrian Relational OLAP Server Engine.
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the Internet backbone.
Multi-access edge computing (MEC), formerly mobile edge computing, is an ETSI-defined network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network and, more in general at the edge of any network. The basic idea behind MEC is that by running applications and performing related processing tasks closer to the cellular customer, network congestion is reduced and applications perform better. MEC technology is designed to be implemented at the cellular base stations or other edge nodes, and enables flexible and rapid deployment of new applications and services for customers. Combining elements of information technology and telecommunications networking, MEC also allows cellular operators to open their radio access network (RAN) to authorized third parties, such as application developers and content providers.
Enhanced Privacy ID (EPID) is Intel Corporation's recommended algorithm for attestation of a trusted system while preserving privacy. It has been incorporated in several Intel chipsets since 2008 and Intel processors since 2011. At RSAC 2016 Intel disclosed that it has shipped over 2.4B EPID keys since 2008. EPID complies with international standards ISO/IEC 20008 / 20009, and the Trusted Computing Group (TCG) TPM 2.0 for authentication. Intel contributed EPID intellectual property to ISO/IEC under RAND-Z terms. Intel is recommending that EPID become the standard across the industry for use in authentication of devices in the Internet of Things (IoT) and in December 2014 announced that it was licensing the technology to third-party chip makers to broadly enable its use.
Smart manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the supply chain, efficient production and recyclability. In this concept, as smart factory has interoperable systems, multi-scale dynamic modelling and simulation, intelligent automation, strong cyber security, and networked sensors.
The Industrial Internet of Things (IIoT) refers to interconnected sensors, instruments, and other devices networked together with computers' industrial applications, including manufacturing and energy management. This connectivity allows for data collection, exchange, and analysis, potentially facilitating improvements in productivity and efficiency as well as other economic benefits. The IIoT is an evolution of a distributed control system (DCS) that allows for a higher degree of automation by using cloud computing to refine and optimize the process controls.
The Internet of Military Things (IoMT) is a class of Internet of things for combat operations and warfare. It is a complex network of interconnected entities, or "things", in the military domain that continually communicate with each other to coordinate, learn, and interact with the physical environment to accomplish a broad range of activities in a more efficient and informed manner. The concept of IoMT is largely driven by the idea that future military battles will be dominated by machine intelligence and cyber warfare and will likely take place in urban environments. By creating a miniature ecosystem of smart technology capable of distilling sensory information and autonomously governing multiple tasks at once, the IoMT is conceptually designed to offload much of the physical and mental burden that warfighters encounter in a combat setting.
Internet of vehicles (IoV) is a network of vehicles equipped with sensors, software, and the technologies that mediate between these with the aim of connecting & exchanging data over the Internet according to agreed standards. IoV evolved from Vehicular Ad Hoc Networks and is expected to ultimately evolve into an "Internet of autonomous vehicles".
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