Abstract: The power consumed by a large IT system may be managed by individual servers calculating a set of predictors of the resources of the large IT system that may be required for a future time period, and weighting factors for those predictors. The predictors and weighting factors may be based on historical data showing actual resources used and past values of the predictors and weighting factors. An estimate of the resources required for the large IT system is then produced based on the predictors and weighting factors and the estimate is then used to determine excess resources of the individual server that may be put into a low power state in the future time period to minimize the power used. If too much resource is excess, the server may enter a soft off state.

Abstract: The power consumed by a large IT system may be managed by individual servers calculating a set of predictors of the resources of the large IT system that may be required for a future time period, and weighting factors for those predictors. The predictors and weighting factors may be based on historical data showing actual resources used and past values of the predictors and weighting factors. An estimate of the resources required for the large IT system is then produced based on the predictors and weighting factors and the estimate is then used to determine excess resources of the individual server that may be put into a low power state in the future time period to minimize the power used. If too much resource is excess, the server may enter a soft off state.

Abstract: A method of computer system security is proposed that uses a failword, which is a password-like string that fools the malicious user, and does not alert him that he is not gaining proper access. A failword is indistinguishable to the malicious user from a password in its apparent functionality, but has a different real utility. Failword security is implemented by picking a set of failwords, by separating the system data into two sets: the open data set which is not protected, and the closed data set which is, by creating a decoy data set that imitates the closed data set, and by suitably updating these sets. The effect of this method is to give the system a strong counter-offensive capability against malicious users, especially useful where significant commercial or national security interests are involved.