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.

On optimising personal network size to manage information flow

Abstract: PN refer to the set of ties a specific individual has with other people. There is significant variation in the size of an individual's PN and this paper explores the effect of variation in PN size on information flow through complete social networks. We analyse degree distributions from two personal network datasets and seek to characterise PN size variations. Random matrix analysis is used to demonstrate that the specific mixture of PN sizes plays an important role in shaping the pattern of information dissemination in complete social networks. To explore this further, we conducted a series of studies on normal random graphs that represent social networks in which PN size follows a normal distribution. We demonstrate that there are three critical parameters which influence how information flows through a social network: the mean PN size, the variance in PN size and the rate at which information passes between nodes in the network. The results suggests that if the rate of information flow is increased, for example by using electronic communication rather than face-to-face communication, this could have a dramatic influence on the probability of an individual acquiring a piece of information from a person in their network.

XORs in the past and future

Abstract: While placing the paper "XORs in the Air" in the context of the theoretical and practical understanding of network coding, we present a view of the progress of the field of network coding, In particular, we examine the interplay of theory and practice in the field.

Surveying the Social, Smart and Converged TV Landscape: Where is Television Research Headed?

Abstract: The TV is dead motto of just a few years ago has been replaced by the prospect of Internet Protocol (IP) television experiences over converged networks to become one of the great technology opportunities in the next few years. As an introduction to the Special Issue on Smart, Social and Converged Television, this extended editorial intends to review the current IP television landscape in its many realizations: operator-based, over-the-top, and user generated. We will address new services like social TV and recommendation engines, dissemination including new paradigms built on peer to peer and content centric networks, as well as the all important quality of experience that challenges services and networks alike. But we intend to go further than just review the existing work by proposing areas for the future of television research. These include strategies to provide services that are more efficient in network and energy usage while being socially engaging, novel services that will provide consumers with a broader choice of content and devices, and metrics that will enable operators and users alike to define the level of service they require or that they are ready to provide. These topics are addressed in this survey paper that attempts to create a unifying framework to link them all together. Not only is television not dead, it is well alive, thriving and fostering innovation and this paper will hopefully prove it.

IP over photons: how not to waste the waist of the hourglass

Abstract: IP is often referred to as the waist of the hourglass, because of the simple model the Internet provides packet level communication compared to other approaches (eg, FR, X25 or B-ISDN), but runs over a complex plethora of links and switched networks, and is used by a firmament of application and transport protocols The ever increasing demand for capacity is pushing us past the 40 Gbit/s barrier, and towards the terabit link Dense mode WDM offers 128 wavelengths at tens of gigabytes per wavelength However re-tuning takes geological epochs compared to IP packet switching, or flow switching, or even QoS routing time frames The problem resembles that of IP over ATM or other virtual circuits, but this may be misleading: what is needed is a novel approach to a network architecture, that avoids the same design flaws and pitfalls we have been forced into in IP over ATM (including MPLS) This paper briefly describes why these approaches are misled, and attempts to outline an approach based on network edge packet sorting and scheduling, which may allow us to use pure optical core networks without sacrificing the flexibility of what we might call legacy electron-datagram services

Learning Reproducibility with a Yearly Networking Contest

Abstract: Better reproducibility of networking research results is currently a major goal that the academic community is striving towards. This position paper makes the case that improving the extent and pervasiveness of reproducible research can be greatly fostered by organizing a yearly international contest. We argue that holding a contest undertaken by a plurality of students will have benefits that are two-fold. First, it will promote hands-on learning of skills that are helpful in producing artifacts at the replicable-research level. Second, it will advance the best practices regarding environments, testbeds, and tools that will aid the tasks of reproducibility evaluation committees by and large.

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.