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We consider the problems of placing or routing the movement of mobile unmanned aircraft for wirelessly relaying traffic, with the goal of enabling the maximum possible bitrate between any pair of clients. We first formalize this as a problem of placing a specified number of relay nodes to create a spanning network that minimizes the maximum link length, and show that approximating the optimum is a...
We describe and demonstrate a fully distributed algorithm that enables prioritized TCP flows to allocate network resources (bandwidth) among themselves. The algorithm does not require any explicit communication among the different TCP flows. It enables autonomous adaptation to loss of network resources due to cyber attack or failure, while ensuring that users receive prioritized utility from available...
We describe and demonstrate fully distributed algorithms that enable cloud clients to select among a set of available computing clusters adaptively, based on measurements of cluster computing loads and the relative bandwidths of paths between the client and each cluster. These techniques are particularly important in cases where (1) clients connect to clusters over stressed wireless networks whose...
ACCORD addresses the need for robust, rapidly adaptive resource allocation mechanisms in cloud computing. It employs a distributed, game-theoretic approach to apportion computational loads in an efficient, prioritized, Pareto-optimal fashion among geographically dispersed cloud computing infrastructure. This paper describes ACCORD algorithms, software implementation, and initial experimental results...
This paper proposes Silent Networking – a new method to significantly increase the lifetimes of energy-constrained nodes, networks, and mobile user devices. With Silent Networking, each network element powers off some or all of its radio interfaces during their naturally occurring silent periods, i.e., time periods when it does not expect to originate, receive, or relay traffic through those interfaces...
A heavy tailed time series that can be represented as an infinite moving average has the property that the sample autocorrelation function (ACF) at lag h converges in probability to a constant ρ(h), although the mathematical correlation typically does not exist. For many nonlinear heavy tailed models, however, the sample ACF at lag h converges in distribution to a nondegenerate random variable. In...
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