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The adaptive resource management framework implemented in the European ACTORS project is presented. A resource manager has been developed that collaborates with a new Linux scheduler providing support for hard constant bandwidth server reservations, in order to adapt applications to changes in resource availability and to adapt the resource allocation to changes in application requirements. The fo
Self-adaptation enables software to execute successfully in dynamic, unpredictable, and uncertain environments. Control theory provides a broad set of mathematically grounded techniques for adapting the behavior of dynamic systems. While it has been applied to specific software control problems, it has proved difficult to define methodologies allowing non-experts to systematically apply control te
The design of a controller for glycemia regulation, either in open or in closed-‐loop, relies on models able to describe the effects of a meal intake and an insulin injection on blood glucose dynamics. The purpose of this study was therefore to propose a physiological relevant yet parsimonious model for carbohydrate action on fasting blood glucose in T1DM patients when no insulin is taken.
This study investigates temporal relationships between vegetation growth, rainfall, and soil moisture for six sites located in sub-Saharan and southern Africa for the period 2005-2009. Specifically, seasonal components of time series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectroradiometer (MODIS) and hal
A number of techniques have been proposed to provide run- time performance guarantees while minimizing power consumption. One drawback of existing approaches is that they work only on a fixed set of components (or actuators) that must be specified at design time. If new components become available, these management systems must be redesigned and reimplemented. In this paper, we propose PTRADE, a n
It has been shown that optimal controller synthesis for positive systems can be formulated as a linear program. Leveraging these results, we propose a scalable iterative algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model. We achieve the desired feedback structure by augmenting the optimization problems w
The problem of resource management in a sys- tem of a-priori unknown software components executing on nondeterministic hardware is considered. The approach uses on-line parameter estimation to address uncertainties and combines this with a convex optimization-based control scheme able to handle overload situations. An algorithm to solve the optimization in real-time is presented together with perf
For interconnected systems and systems of large size, aggregating information of subsystems studied individually is useful for addressing the overall stability. In the Lyapunov- based analysis, summation and maximization of separately constructed functions are two typical approaches in such a philosophy. This paper focuses on monotone systems which are common in control applications and elucidates
This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sides
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
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
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
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
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
