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Alexandria, Australia

NICTA is Australia's Information and Communications Technology Research Centre of Excellence. The term "Centre of Excellence" is common marketing terminology used by some Australian government organisations for titles of science research groups. NICTA's role is to pursue potentially economically significant ICT related research for the Australian economy.NICTA's organisation is structured around groups focused primarily on pure research and the implementation of those ideas within business groups. Wikipedia.

Brebner P.,NICTA
ICPE'12 - Proceedings of the 3rd Joint WOSP/SIPEW International Conference on Performance Engineering

Elasticity, the ability to rapidly scale resources up and down on demand, is an essential feature of public cloud platforms. However, it is difficult to understand the elasticity requirements of a given application and workload, and if the elasticity provided by a cloud provider will meet those requirements. We introduce the elasticity mechanisms of a typical Infrastructure as a Service (IaaS) cloud platform (inspired by Amazon EC2). We have enhanced our Service Oriented Performance Modeling method and tool to model and predict the elasticity characteristics of three realistic applications and workloads on this cloud platform. We compare the pay-as-you-go instance costs and end-user response time service level agreements for different elasticity scenarios. The model is also able to predict the elasticity requirements (in terms of the maximum instance spin-up time) for the three applications. We conclude with an analysis of the results. Copyright 2012 ACM. Source

Perriollat M.,VI Technology | Hartley R.,NICTA | Bartoli A.,University dAuvergne
International Journal of Computer Vision

We present a monocular 3D reconstruction algorithm for inextensible deformable surfaces. It uses point correspondences between a single image of the deformed surface taken by a camera with known intrinsic parameters and a template. The main assumption we make is that the surface shape as seen in the template is known. Since the surface is inextensible, its deformations are isometric to the template. We exploit the distance preservation constraints to recover the 3D surface shape as seen in the image. Though the distance preservation constraints have already been investigated in the literature, we propose a new way to handle them. Spatial smoothness priors are easily incorporated, as well as temporal smoothness priors in the case of reconstruction from a video. The reconstruction can be used for 3D augmented reality purposes thanks to a fast implementation. We report results on synthetic and real data. Some of them are compared to stereo-based 3D reconstructions to demonstrate the efficiency of our method. © 2010 Springer Science+Business Media, LLC. Source

Zaidi Z.R.,NICTA | Mark B.L.,George Mason University
IEEE Transactions on Mobile Computing

We propose an integrated scheme for tracking the mobility of a user based on autoregressive models that accurately capture the characteristics of realistic user movements in wireless networks. The mobility parameters are obtained from training data by computing Minimum Mean Squared Error (MMSE) estimates. Estimation of the mobility state, which incorporates the position, velocity, and acceleration of the mobile station, is accomplished via an extended Kalman filter using signal measurements from the wireless network. By combining mobility parameter and state estimation in an integrated framework, we obtain an efficient and accurate real-time mobility tracking scheme that can be applied in a variety of wireless networking applications. We consider two variants of an autoregressive mobility model in our study and validate the proposed mobility tracking scheme using mobile trajectories collected from drive test data. Our simulation results validate the accuracy of the proposed tracking scheme even when only a small number of data samples is available for initial training. © 2011 IEEE. Source

Tricoire F.,University of Vienna | Tricoire F.,NICTA
Computers and Operations Research

This paper introduces multi-directional local search, a metaheuristic for multi-objective optimization. We first motivate the method and present an algorithmic framework for it. We then apply it to several known multi-objective problems such as the multi-objective multi-dimensional knapsack problem, the bi-objective set packing problem and the bi-objective orienteering problem. Experimental results show that our method systematically provides solution sets of comparable quality with state-of-the-art methods applied to benchmark instances of these problems, within reasonable CPU effort. We conclude that the proposed algorithmic framework is a viable option when solving multi-objective optimization problems. © 2012 Elsevier Ltd. All rights reserved. Source

Walsh T.,NICTA
Journal of Artificial Intelligence Research

Voting is a simple mechanism to combine together the preferences of multiple agents. Unfortunately, agents may try to manipulate the result by mis-reporting their preferences. One barrier that might exist to such manipulation is computational complexity. In particular, it has been shown that it is NP-hard to compute how to manipulate a number of different voting rules. How- ever, NP-hardness only bounds the worst-case complexity. Recent theoretical results suggest that manipulation may often be easy in practice. In this paper, we show that empirical studies are useful in improving our understanding of this issue. We consider two settings which represent the two types of complexity results that have been identified in this area: manipulation with un- weighted votes by a single agent, and manipulation with weighted votes by a coalition of agents. In the first case, we consider Single Transferable Voting (STV), and in the second case, we consider veto voting. STV is one of the few voting rules used in practice where it is NP-hard to compute how a single agent can manipulate the result when votes are unweighted. It also appears one of the harder voting rules to manipulate since it involves multiple rounds. On the other hand, veto voting is one of the simplest representatives of voting rules where it is NP-hard to compute how a coalition of weighted agents can manipulate the result. In our experiments, we sample a number of distributions of votes including uniform, correlated and real world elections. In many of the elections in our experiments, it was easy to compute how to manipulate the result or to prove that manipulation was impossible. Even when we were able to identify a situation in which manipula- tion was hard to compute (e.g. when votes are highly correlated and the election is \hung"), we found that the computational diffculty of computing manipulations was somewhat precarious (e.g. with such \hung" elections, even a single uncorrelated voter was enough to make manipulation easy to compute). © 2011 AI Access Foundation. All rights reserved. Source

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