214 resultados para OpenStack DevStack Migration Cold_Migration Live_Migration Cloud IaaS


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This paper is prompted by the widespread acceptance that the rates of inter-county and inter-state migration have been falling in the USA and sets itself the task of examining whether this decline in migration intensities is also the case in the UK. It uses annual inter-area migration matrices available for England and Wales since the 1970s by broad age group. The main methodological challenge, arising from changes in the geography of health areas for which the inter-area flows are given, is addressed by adopting the lowest common denominator of 80 areas. Care is also taken to allow for the effect of economic cycles in producing short-term fluctuations on migration rates and to isolate the effect of a sharp rise in rates for 16-24 year olds in the 1990s, which is presumed to be related to the expansion of higher education. The findings suggest that, unlike for the USA, there has not been a substantial decline in the intensity of internal migration between the first two decades of the study period and the second two. If there has been any major decline in the intensity of address changing in England and Wales, it can only be for the within-area moves that this time series does not cover. This latter possibility is examined in a companion paper using a very different data set (Champion and Shuttleworth, 2016).

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Expectations of migration and mobility steadily increasing in the longer term, which have a long currency in migration theory and related social science, are at odds with the latest US research showing a marked decline in internal migration rates. This paper reports the results of research that investigates whether England and Wales have experienced any similar change in recent decades. Using the Office for National Statistics Longitudinal Study (ONS-LS) of linked census records, it examines the evidence provided by its 10-year migration indicator, with particular attention to a comparison of the first and latest decades available, 1971-1981 and 2001-2011. This suggests that, as in the USA, there has been a marked reduction in the level of shorter-distance (less than 10km) moving that has involved almost all types of people. In contrast to this and to US experience, however, the propensity of people to make longer-distance address changes between decennial censuses has declined much less, largely corroborating the results of a companion study tracking the annual trend in rates of between-area migration since the 1970s (Champion and Shuttleworth, 2016).

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Scheduling jobs with deadlines, each of which defines the latest time that a job must be completed, can be challenging on the cloud due to incurred costs and unpredictable performance. This problem is further complicated when there is not enough information to effectively schedule a job such that its deadline is satisfied, and the cost is minimised. In this paper, we present an approach to schedule jobs, whose performance are unknown before execution, with deadlines on the cloud. By performing a sampling phase to collect the necessary information about those jobs, our approach delivers the scheduling decision within 10% cost and 16% violation rate when compared to the ideal setting, which has complete knowledge about each of the jobs from the beginning. It is noted that our proposed algorithm outperforms existing approaches, which use a fixed amount of resources by reducing the violation cost by at least two times.