messages are limited to 18 % of all transmissions. At scale, the protocol exposes interesting propagation dynamics only hinted at by previous dissemination work. A simple model is also derived which describes the limits of data propagation in wireless networks. Finally, we argue that the rates obtained

(movements). The corresponding force concept is discussed in more detail and can be also applied to the description of other behaviors. In the presented model of pedestrian behavior several force terms are essential: First, a term describing the acceleration towards the desired velocity of motion. Second

their own course. Each simulated bird is implemented as an independent actor that navigates according to its local perception of the dynamic environment, the laws of simulated physics that rule its motion, and a set of behaviors programmed into it by the "animator." The aggregate motion

The large-scale behavior of routing in the Internet has gone virtually without any formal study, the exception being Chinoy's analysis of the dynamics of Internet routing information [Ch93]. We report on an analysis of 40,000 end-to-end route measurements conducted using repeated “traceroutes

This paper proposes a new logic programming language called GOLOG whose interpreter automatically maintains an explicit representation of the dynamic world being modeled, on the basis of user supplied axioms about the preconditions and effects of actions and the initial state of the world

Abstract We discuss findings from a large-scale study of Internet packet dynamics conducted by tracing 20,000 TCP bulk transfers between 35 Internet sites. Because we traced each 100 Kbyte transfer at both the sender and the receiver, the measurements allow us to distinguish between the end

Multi-threaded programming is difficult and error prone. It is easy to make a mistake in synchronization that produces a data race, yet it can be extremely hard to locate this mistake during debugging. This paper describes a new tool, called Eraser, for dynamically detecting data races in lock

and classifying dynamic behaviors, popular because they offer dynamic time warping, a training algorithm, and a clear Bayesian semantics. However, the Markovian framework makes strong restrictive assumptions about the system generating the signal---that it is a single process having a small number of states

original, uninstrumented behavior. Pin uses dynamic compilation to instrument executables while they are running. For efficiency, Pin uses several techniques, including inlining, register re-allocation, liveness analysis, and instruction scheduling to optimize instrumentation. This fully automated approach

are challenging problems due to the considerable diversity, large numbers, dynamic behavior, and geographical distribution of the entities in which a user might be interested. Consequently, information services are a vital part of any Grid software infrastructure, providing fundamental mechanisms for discovery