An Inhomogeneous Hidden Markov Model for Efficient Virtual Machine Placement in Cloud Computing Environments

In a cloud environment virtual machines are created with different purposes, such as providing users with computers or handling web traffic. A virtual machine is created in such a way that a user will not notice any difference from working on a physical computer. A challenging problem in cloud computing is how to distribute the virtual machines on a set of physical servers. An optimal solution will provide each virtual machine with enough resources and at the same time not using more physical services (energy/electricity) than necessary to achieve this. In this paper we investigate how forecasting of future resource requirements (CPU consumption) for each virtual machine can be used to improve the virtual machine placement on the physical servers. We demonstrate that a time‐dependent hidden Markov model with an autoregressive observation process replicates the properties of the CPU consumption data in a realistic way and forecasts future CPU consumption efficiently. Copyright © 2016 John Wiley & Sons, Ltd.     

Linking climate change to lemming cycles

The population cycles of rodents at northern latitudes have puzzled people for centuries, and their impact is manifest throughout the alpine ecosystem. Climate change is known to be able to drive animal population dynamics between stable and cyclic phases, and has been suggested to cause the recent changes in cyclic dynamics of rodents and their predators. But although predator-rodent interactions are commonly argued to be the cause of the Fennoscandian rodent cycles, the role of the environment in the modulation of such dynamics is often poorly understood in natural systems. Hence, quantitative links between climate-driven processes and rodent dynamics have so far been lacking. Here we show that winter weather and snow conditions, together with density dependence in the net population growth rate, account for the observed population dynamics of the rodent community dominated by lemmings (Lemmus lemmus) in an alpine Norwegian core habitat between 1970 and 1997, and predict the observed absence of rodent peak years after 1994. These local rodent dynamics are coherent with alpine bird dynamics both locally and over all of southern Norway, consistent with the influence of large-scale fluctuations in winter conditions. The relationship between commonly available meteorological data and snow conditions indicates that changes in temperature and humidity, and thus conditions in the subnivean space, seem to markedly affect the dynamics of alpine rodents and their linked groups. The pattern of less regular rodent peaks, and corresponding changes in the overall dynamics of the alpine ecosystem, thus seems likely to prevail over a growing area under projected climate change.     

Perception: Embodiment and Beyond

In this commentary on Don Ihde’s paper “Stretching the in-between: embodiment and beyond” I argue that perceptions and observations are based on tacit frames and these frames are expressed through pre-reflexive intuitions thus giving meaning to the perceived content of observations. However, if the objective or given information in perception is incomplete or missing our brain and nervous system will intuitively and unconsciously fill in the missing information in order to act—these particular pieces of added information may not be relevant to the decoding of the given content of perception at all.