Jon Crowcroft

Bio: Jon Crowcroft is an academic researcher from University of Cambridge. The author has contributed to research in topics: The Internet & Multicast. The author has an hindex of 87, co-authored 672 publications receiving 38848 citations. Previous affiliations of Jon Crowcroft include Memorial University of Newfoundland & Information Technology University.

Edge Intelligence: Empowering Intelligence to the Edge of Network

Abstract: Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.

Ubiquitous Computing: Experience, Design and Science

Abstract: The emergence of powerful digital infrastructures, wireless networks and mobile devices has already started to move computing away from the desktop and embed it in the public spaces, architectures, furniture and personal fabric of everyday life. Handheld and wearable computers, mobile phones, digital cameras, satellite navigation, and a host of similar devices join the Personal Computer as commonplace digital tools. We are increasingly becoming accustomed to using a heterogeneous collection of computing devices to support a growing range of activities. These embryonic forms of ubiquitous computing technology have already had a major impact on the ways that people work, learn, entertain themselves, and interact.

Why Do I Retweet It? An Information Propagation Model for Microblogs

Abstract: Microblogging platforms are Web 2.0 services that represent a suitable environment for studying how information is propagated in social networks and how users can become influential. In this work we analyse the impact of the network features and of the users' behaviour on the information diffusion. Our analysis highlights a strong relation between the level of visibility of a message in the flow of information seen by a user and the probability that the user further disseminates the message. In addition, we also highlight the existence of other latent factors that impact on the dissemination probability, correlated with the properties of the user that generated the message. Considering these results we define an information propagation model that generates information cascades (i.e. flows of messages propagated from user to user) whose statistical properties match empirical observations.

QoS-sensitive flows: issues in IP packet handling

Abstract: IP-based networks were never designed for real time traffic, yet QoS support in such networks is needed to accommodate both global use and the more demanding applications now emerging. Changes in packet handling, in particular, will help provide QoS support in IP networks. The article focuses on the issues and principles concerning router modification for IP packet handling.

Open Distributed Systems

Abstract: From the Publisher: Gain a detailed understanding of the present and future states of distributed systems, using the recently ratified Open Distributed Processing models as a basis. This new book's comprehensive coverage of distributed systems from the ODP perspective gives you a fresh grasp of the applications enabled by distributed systems and demonstrates how: ? A multimedia conferencing system can be built as a distributed application ? Management can be modeled as a distributed application ? A distributed file system can be built as an example of a user application Each chapter of Open Distributed Systems covers a different aspect of the technology, allowing you to read most chapters independently and quickly home in on the information you need. Featuring approximately 60 illustrations, 30 equations and 100 references, this book is a comprehensive text for students, and a practical guide for engineers.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Community detection in graphs

Abstract: The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.