Pervasive computing: vision and challenges

By Mahadev Satyanarayanan. IEEE wireless communications, 2001

2,787 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/c9b9a6dee0f45461d15a32fb7f97dea57a035ea1

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In Computer Networks and Communications

In Computer Vision and Pattern Recognition

Citations in the corpus

Toward an affect-sensitive multimodal human-computer interaction (2003, background): “Namely, since it is generally thought that pervasive computing devices will be all around us in the future [99], it will be inefficient if the user should train each of those devices separately.”
Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges (2014, background): “Alternatively, application offloading [3] and fidelity adaptation [59] approaches are proposed to conserve local mobile resources, especially energy.”
Conceptualizing smart service systems (2017, background): “With the advent of the Internet of Things, embedded systems in physical objects became connected to a world-wide communication network, providing data to and receiving data from other devices and information systems.”
The case for cyber foraging (2002, background): “We conjecture that cyber foraging, construed as “living off the land”, may be an effective way to solve this dilemma [8].”
Location, Localization, and Localizability (2010, background): “For example, pervasive medical care is designed to accurately record and manage patient movements[1-2]; smart space enables the interaction between physical space and human activities[3-4]; modern logistics has major concerns on goods transportation, inventory, and warehousing[5-6]; environmental mo”
Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges (2013, methodology): “Indeed, empowering computation capabilities of mobile devices is not a new concept and there have been different approaches to achieve this goal, including load sharing [4] , remote execution [5], cyber foraging [6], and computation offloading [60], [61] that are described as follows.”
IoT in the Fog: A Roadmap for Data-Centric IoT Development (2018, neutral): “data”
Fast app launching for mobile devices using predictive user context (2012, methodology): “FALCON uses novel features derived through extensive data analysis, and a novel cost-bene.t learning algorithm that has strong predictive performance and low runtime overhead.”
Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones (2012, background): “Existing research [14], [2], [13], [4], [5], [17] has proposed a variety of application-offioading mechanisms.”
SmartPDR: Smartphone-Based Pedestrian Dead Reckoning for Indoor Localization (2015, background): “Thus, localization is essential function needed by location-aware applications in pervasive computing environments [1], [2].”
A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing (2013, background): “The term cyber foraging is introduced by Satyanarayanan [29] to augment the computing potentials of wireless mobile devices by exploiting available stationary computers in the local environment.”
Challenges and Solutions of Ubiquitous User Modeling (2012, background): “In parallel with the various solutions being proposed, new models, visions and challenges continue to appear [1, 35, 55, 70, 72, 87, 89].”