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.

Partisan Sharing: Facebook Evidence and Societal Consequences

Abstract: The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news articles and avoid conflicting ones. We verified four main hypotheses. That is, whether partisan sharing: 1) exists at all; 2) changes across individuals (e.g., depending on their interest in politics); 3) changes over time (e.g., around elections); and 4) changes depending on perceived importance of topics. We indeed find strong evidence for partisan sharing. To test whether it has any consequence in the real world, we built a web application for BBC viewers of a popular political program, resulting in a controlled experiment involving more than 70 individuals. Based on what they share and on survey data, we find that partisan sharing has negative consequences: distorted perception of reality. However, we do also find positive aspects of partisan sharing: it is associated with people who are more knowledgeable about politics and engage more with it as they are more likely to vote in the general elections.

Statistical mechanics of rumour spreading in network communities

Abstract: We report a preliminary investigation on interactions between networked social communities using the Ising model to analyze the spread of rumours. The inner opinion of a given community is forced to change through the introduction of a unique external source and we analyze how the other communities react to this change. We model two conceptual external sources: namely, “Strong-belief ”, and “Propaganda”, by an infinitely strong inhomogeneous external field and a finite uniform external field, respectively. In the former case, the community changes independently from other communities while in the latter case according also to interactions with the other communities. We apply our model to synthetic networks as well as various real world data ranging from human physical contact networks to online social networks. The experimental results using real world data clearly demonstrate two distinct scenarios of phase transitions.

Emu: rapid prototyping of networking services

Abstract: Due to their performance and flexibility, FPGAs are an attractive platform for the execution of network functions. It has been a challenge for a long time though to make FPGA programming accessible to a large audience of developers. An appealing solution is to compile code from a general-purpose language to hardware using high-level synthesis. Unfortunately, current approaches to implement rich network functionality are insufficient because they lack: (i) libraries with abstractions for common network operations and data structures, (ii) bindings to the underlying "substrate" on the FPGA, and (iii) debugging and profiling support. This paper describes Emu, a new standard library for an FPGA hardware compiler that enables developers to rapidly create and deploy network functionality. Emu allows for high-performance designs without being bound to particular packet processing paradigms. Furthermore, it supports running the same programs on CPUs, in Mininet, and on FPGAs, providing a better development environment that includes advanced debugging capabilities. We demonstrate that network functions implemented using Emu have only negligible resource and performance overheads compared with natively-written hardware versions.

Component framework infrastructure for virtual environments

Abstract: Virtual Environments (VE) present a complex problem with interesting non-trivial challenges for system development, in particular when the VE is distributed and shared amongst multiple participants. Most problems are common to any VE system, however the development effort is replicated because current systems are neither evolutionary nor allow integration of code across different systems.This paper presents the Java Adaptive Dynamic Environment (JADE), which consists of a light-weight cross-platform kernel with inherent capabilities for dynamic extensibility in run-time. This kernel is the embodiment of a component framework for the underlying infrastructure of VE systems, addressing the problems of evolution and integration.

Implementation of Smart Contracts Using Hybrid Architectures with On and Off–Blockchain Components

Abstract: Decentralised (on-blockchain) and centralised (off–blockchain) platforms are available for the implementation of smart contracts. However, none of the two alternatives can individually provide the services and quality of services (QoS) imposed on smart contracts involved in a large class of applications. The reason is that blockchain platforms suffer from scalability, performance, transaction costs and other limitations. Likewise, off–blockchain platforms are afflicted by drawbacks emerging from their dependence on single trusted third parties. We argue that in several applications, hybrid platforms composed from the integration of on and off–blockchain platforms are more adequate. Developers that informatively choose between the three alternatives are likely to implement smart contracts that deliver the expected QoS. Hybrid architectures are largely unexplored. To help cover the gap and as a proof of concept, in this paper we discuss the implementation of smart contracts on hybrid architectures. We show how a smart contract can be split and executed partially on an off–blockchain contract compliance checker and partially on the rinkeby ethereum network. To test the solution, we expose it to sequences of contractual operations generated mechanically by a contract validator tool.

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.