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.

Delivery Properties of Human Social Networks

Abstract: The recently proposed packet switched network paradigm takes advantage of human social contacts to opportunistically create data paths over time. Our goal is to examine the effect of the human contact process on data delivery. We find that the contact occurrence distribution is highly uneven: contacts between a few node-pairs occur too frequently, leading to inadequate mixing in the network, while the majority of contacts are rare, and essential for connectivity. This distribution of contacts leads to a significant variation in performance over short time windows. We discover that the formation of a large clique core during the window is correlated with the fraction of data delivered, as well as the speed of delivery. We then show that the clustering co-efficient of the contact graph over a time window is a good predictor of performance during the window. Taken together, our findings suggest new directions for designing forwarding algorithms in ad-hoc or delay-tolerant networking schemes using humans as data mules.

A Dynamic Sender-Initiated Reservation Protocol for the Internet

Abstract: In this paper we discuss the need for resource reservation in the Internet and examine some of the strengths and weaknesses of RSVP, which is currently the most popular of Internet reservation protocols that have been developed. The deficiencies of RSVP motivate our design of a new resource reservation protocol which uses dynamic sender-initiated reservations to achieve a highly bandwidth-efficient reservation mechanism with excellent scalability with regards to round trip time, data rate and number of hosts.

Blockchain for economically sustainable wireless mesh networks

Abstract: This is the peer reviewed version of the following article: Kabbinale, AR, Dimogerontakis, E, Selimi, M, et al. Blockchain for economically sustainable wireless mesh networks. Concurrency Computat Pract Exper. 2020; 32:e5349, which has been published in final form at https://doi.org/10.1002/cpe.5349. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Understanding Internet Usage and Network Locality in a Rural Community Wireless Mesh Network

Abstract: Community networks owned and operated by local communities have recently gained popularity as a low cost solution for Internet access. In this paper, we seek to understand the characteristics of Internet usage in community networks and provide useful insights on designing and improving community networks in rural areas. We report the results of a socio-technical study carried out during a three month measurement of a community wireless mesh network (CWMN) which has been operating for two years in a rural area of northern Thailand. An on-site social interview was also conducted to supplement our analysis. The results reveal several interesting findings: rural users do use online social networks, instant messaging applications and online games similarly to urban users; they install unnecessary applications on their mobile phones and are completely obvious to their side effects -- the traffic from these applications accounts for a major share of the traffic leading to numerous network anomalies. Finally our analysis uncovers the characteristic of locality in community networks where users in close geographical proximity interact with each other.

CRAM: cell re-labeling at merge-points for ATM multicast

Abstract: Many distributed multimedia applications involve data delivery from a source to multiple destinations, the participating nodes forming a multicast group. In the naive solution, separate connections can be established from each source to other group members. However a tree can be established for each source with the participants as the leaf nodes or just have one tree spanning all the participants. In this paper, we introduce a data forwarding model to support such shared multicast trees over the ATM networks called CRAM (cell re-labeling at merge-points for ATM multicast). Our work allows VC merging in the MPLS architecture and supports recently proposed wide area multicast protocols (like CBT and PIM) in ATM networks.

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.