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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.


Papers
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TL;DR: It is argued that most of the pieces of technology needed for building a barter system are now available, including blockchains, smart contracts, cryptography, secure multiparty computations and fair exchange protocols, however, additional research is needed to refine and integrate the pieces together.
Abstract: We suggest the re-introduction of bartering to create a cryptocurrencyless, currencyless, and moneyless economy segment. We contend that a barter economy would benefit enterprises, individuals, governments and societies. For instance, the availability of an online peer-to-peer barter marketplace would convert ordinary individuals into potential traders of both tangible and digital items and services. For example, they will be able to barter files and data that they collect. Equally motivating, they will be able to barter and re-introduce to the economy items that they no longer need such as, books, garden tools, and bikes which are normally kept and wasted in garages and sheds. We argue that most of the pieces of technology needed for building a barter system are now available, including blockchains, smart contracts, cryptography, secure multiparty computations and fair exchange protocols. However, additional research is needed to refine and integrate the pieces together. We discuss potential research directions.

3 citations

Proceedings ArticleDOI
TL;DR: In this paper, the authors propose a decentralized protocol and architecture for discovering radio devices over the Internet, which has low resource requirements, making it suitable for implementation on limited platforms, and evaluate the protocol through simulation in network topologies with up to 2.3 million nodes, including topologies generated from population patterns.
Abstract: Scarcity of frequencies and the demand for more bandwidth is likely to increase the need for devices that utilize the available frequencies more efficiently. Radios must be able to dynamically find other users of the frequency bands and adapt so that they are not interfered, even if they use different radio protocols. As transmitters far away may cause as much interference as a transmitter located nearby, this mechanism can not be based on location alone. Central databases can be used for this purpose, but require expensive infrastructure and planning to scale. In this paper, we propose a decentralized protocol and architecture for discovering radio devices over the Internet. The protocol has low resource requirements, making it suitable for implementation on limited platforms. We evaluate the protocol through simulation in network topologies with up to 2.3 million nodes, including topologies generated from population patterns in Norway. The protocol has also been implemented as proof-of-concept in real Wi-Fi routers.

3 citations

Proceedings ArticleDOI
25 May 2015
TL;DR: This paper studies the problem of efficient data recovery using the data mules approach, where a set of mobile sensors with advanced mobility capabilities re-acquire lost data by visiting the neighbors of failed sensors, thereby improving network resiliency.
Abstract: In this paper, we study the problem of efficient data recovery using the data mules approach, where a set of mobile sensors with advanced mobility capabilities re-acquire lost data by visiting the neighbors of failed sensors, thereby improving network resiliency. Our approach involves defining the optimal communication graph and mules' placements such that the overall traveling time and distance is minimized regardless to which sensors crashed. We explore this problem under different practical network topologies such as general graphs, grids and random linear networks and provide approximation algorithms based on multiple combinatorial techniques. Simulation experiments demonstrate that our algorithms outperform various competitive solutions for different network models, and that they are applicable for practical scenarios.

3 citations

Book
01 Jan 2001
TL;DR: This paper focuses on application-level Multicast using Content-Addressable Networks, and the design of a large-scale Event Notification Infrastructure for Large-Scale Group Communication.
Abstract: Application-Level.- Latency and User Behaviour on a Multiplayer Game Server.- Application-Level Multicast Using Content-Addressable Networks.- Scribe: The Design of a Large-Scale Event Notification Infrastructure.- Group Management.- Scamp: Peer-to-Peer Lightweight Membership Service for Large-Scale Group Communication.- Extremum Feedback for Very Large Multicast Groups.- An Overlay Tree Building Control Protocol.- Performance.- The Multicast Bandwidth Advantage in Serving a Web Site.- STAIR: Practical AIMD Multirate Multicast Congestion Control.- Impact of Tree Structure on Retransmission Efficiency for TRACK.- Security.- Framework for Authentication and Access Control of Client-Server Group Communication Systems.- Scalable IP Multicast Sender Access Control for Bi-directional Trees.- EHBT: An Efficient Protocol for Group Key Management.- Topology.- Aggregated Multicast with Inter-Group Tree Sharing.- Tree Layout for Internal Network Characterizations in Multicast Networks.

3 citations

Proceedings ArticleDOI
25 Jun 2012
TL;DR: This work formally defines the problem to construct the optimal channel ordering which minimizes the seek distance in selecting channels and shows this problem is NP-hard and presents a reasonable heuristic to solve this problem.
Abstract: Increases in the number of TV channels requires users to spend more time to select their preferred channels since the user interaction for browsing is practically limited to the conventional remote control with a two-way scrolling button. We formally define the problem to construct the optimal channel ordering which minimizes the seek distance in selecting channels and show this problem is NP-hard. In addition, we present a reasonable heuristic to solve this problem. The proposed method constructs an efficient channel ordering by applying a hierarchical clustering algorithm based on the frequencies of switching events between channels. We demonstrate the feasibility of this method by applying a number of well-known hierarchical clustering algorithms and evaluating the number of user inputs required for selecting channels. Our experimental results show that the proposed method significantly decreases the number of user inputs compared with the conventional methods.

3 citations


Cited by
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Journal ArticleDOI

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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
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 …

33,785 citations

Journal ArticleDOI
TL;DR: In this paper, Imagined communities: Reflections on the origin and spread of nationalism are discussed. And the history of European ideas: Vol. 21, No. 5, pp. 721-722.

13,842 citations

Journal ArticleDOI
TL;DR: A thorough exposition of community structure, or clustering, is attempted, 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.
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.

9,057 citations

Journal ArticleDOI
TL;DR: A thorough exposition of the main elements of the clustering problem can be found in this paper, 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.

8,432 citations