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PCP: A Generalized Approach to Optimizing Performance Under Power Constraints through Resource Management

Many computing systems are constrained by power budgets. While they could temporarily draw more power, doing so creates unsustainable temperatures and unwanted electricity consumption. Developing systems that operate within power budgets is a constrained optimization problem: configuring the components within the system to maximize performance while maintaining sustainable power consumption. This

Brownout: Building More Robust Cloud Applications

Self-adaptation is a first class concern for cloud applications, which should be able to withstand diverse runtime changes. Variations are simultaneously happening both at the cloud infrastructure level - for example hardware failures - and at the user workload level - flash crowds. However, robustly withstanding extreme variability, requires costly hardware over-provisioning. In this paper, we i

On Structured Realizability and Stabilizability of Linear Systems

We study the notion of structured realizability for linear systems dened over graphs. A stabilizable and detectable realization is structured if the state-space matrices inherit the sparsity pattern of the adjacency matrix of the associated graph. In this paper, we demonstrate that not every structured transfer matrix has a structured realization and we reveal the practical meaning of this fact. W

A control-theoretical approach to thread scheduling for multicore processors

Feedback control has been applied to computing systems, usually taking a designed system and closing a loop to adjust some of its parameters. However, the design of computing systems components as controllers have shown advantages with respect to state-of-the-art techniques, especially in the scheduling domain, where uniprocessor schedulers have been designed as discrete-time control structures. H

On the Kalman-Yakubovich-Popov Lemma for Positive Systems

An extended Kalman-Yakubovich-Popov (KYP) Lemma for positive systems is derived. The main difference compared to earlier versions is that non-strict inequalities are treated. Matrix assumptions are also less restrictive. Moreover, a new equivalence is introduced in terms of linear programming rather than semi-definite programming. As a complement to the KYP lemma, it is also proved that a symmetri

Learning Based Image Segmentation of Pigs in a Pen

As farms are getting bigger with more animals, less manual supervision and attention can be given the animals on both group and individual level. In order not to jeopardize animal welfare, automated supervision is in some way already in use. Function and control of ventilation is already in use in modern pig stables, e.g. by the use of sensors for temperature, relative humidity and malfunction con

A knowledge integration framework for robotics

This paper describes a knowledge integration framework for robotics, whose goal is to represent, store, adapt, and distribute knowledge across engineering platforms. The architecture abstracts the components as data sources, where data are available in the AutomationML data exchange format. AutomationML is an on-going standard initiative that aims at unifying data representation and APIs used by e

Distributed Receding Horizon Kalman Filter

In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the agents by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mob

Combining parallel search and parallel consistency in constraint programming

Program parallelization becomes increasingly important when new multi-core architectures provide ways to improve performance. One of the greatest challenges of this development lies in programming parallel applications. Declarative languages, such as constraint programming, can make the transition to parallelism easier by hiding the parallelization details in a framework. Automatic parallelizatio

Distributed averaging on digital noisy networks

We consider a class of distributed algorithms for computing arithmetic averages (average consensus) over net- works of agents connected through digital noisy broadcast channels. Our algorithms combine error-correcting codes with the classical linear consensus iterative algorithm, and do not require the agents to have knowledge of the global network structure. We improve the performance by introduc

Processor Thermal Control Using Adaptive Bandwidth Resource Management

An adaptive resource management system combined with a thermal controller is presented. The aim of the system is to dynamically allocate computing resources to applications competing for the same computing resources in such a way that the system is not overheated. The approach has been implemented on a mobile robot. Experimental results are presented showing the feasibility of the approach.