Maxwell Young
University of Waterloo
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Publication
Featured researches published by Maxwell Young.
Journal of Conflict Resolution | 2007
Aaron Clauset; Maxwell Young; Kristian Skrede Gleditsch
In the spirit of Lewis Richardson’s original study of the statistics of deadly conflicts, we study the frequency and severity of terrorist attacks worldwide since 1968. We show that these events are uniformly characterized by the phenomenon of “scale invariance,” that is, the frequency scales as an inverse power of the severity, P(x) Αx-α. We find that this property is a robust feature of terrorism, persisting when we control for economic development of the target country, the type of weapon used, and even for short time scales. Further, we show that the center of the distribution oscillates slightly with a period of roughly τ≈ 13 years, that there exist significant temporal correlations in the frequency of severe events, and that current models of event incidence cannot account for these variations or the scale invariance property of global terrorism. Finally, we describe a simple toy model for the generation of these statistics and briefly discuss its implications.
european symposium on algorithms | 2005
Amos Fiat; Jared Saia; Maxwell Young
Chord is a distributed hash table (DHT) that requires only O(log n) links per node and performs searches with latency and message cost O(log n), where n is the number of peers in the network. Chord assumes all nodes behave according to protocol. We give a variant of Chord which is robust with high probability for any time period during which: 1) there are always at least z total peers in the network for some integer z; 2) there are never more than (1/4–e)z Byzantine peers in the network for a fixed e > 0; and 3) the number of peer insertion and deletion events is no more than zk for some tunable parameter k. We assume there is an adversary controlling the Byzantine peers and that the IP-addresses of all the Byzantine peers and the locations where they join the network are carefully selected by this adversary. Our notion of robustness is rather strong in that we not only guarantee that searches can be performed but also that we can enforce any set of “proper behavior” such as contributing new material, etc. In comparison to Chord, the resources required by this new variant are only a polylogarithmic factor greater in communication, messaging, and linking costs.
international conference on distributed computing systems | 2010
Maxwell Young; Aniket Kate; Ian Goldberg; Martin Karsten
There are several analytical results on distributed hash tables (DHTs) that can tolerate Byzantine faults. Unfortunately, in such systems, operations such as data retrieval and message sending incur significant communication costs. For example, a simple scheme used in many Byzantine fault-tolerant DHT constructions of
Information Processing Letters | 2007
Michael J. Collins; David Kempe; Jared Saia; Maxwell Young
n
IEEE Communications Surveys and Tutorials | 2011
Maxwell Young; Raouf Boutaba
nodes requires
Cooperation and Conflict | 2010
Aaron Clauset; Lindsay Heger; Maxwell Young; Kristian Skrede Gleditsch
O(\log^{3}n)
Information Processing Letters | 2008
Jared Saia; Maxwell Young
messages, this is likely impractical for real-world applications. The previous best known message complexity is
principles of distributed computing | 2011
Valerie King; Jared Saia; Maxwell Young
O(\log^2{n})
Information Processing Letters | 2007
Shuang Luan; Jared Saia; Maxwell Young
{\it in expectation}, however, the corresponding protocol suffers from prohibitive costs owing to hidden constants in the asymptotic notation and setup costs. In this paper, we focus on reducing the communication costs against a computationally bounded adversary. We employ threshold cryptography and distributed key generation to define two protocols both of which are more efficient than existing solutions. In comparison, our first protocol is {\it deterministic} with
IEEE ACM Transactions on Networking | 2013
Maxwell Young; Aniket Kate; Ian Goldberg; Martin Karsten
O(\log^2{}n)