The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterpri...The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterprise data center requires a significant amount of time and human effort. Following a major disruption, the recovery process involves multiple stages, and during each stage, the partially recovered infrastructures can provide limited services to users at some degraded service level. However, how fast and efficiently an enterprise infrastructure can be recovered de- pends on how the recovery mechanism restores the disrupted components, considering the inter-dependencies between services, along with the limitations of expert human operators. The entire problem turns out to be NP- hard and rather complex, and we devise an efficient meta-heuristic to solve the problem. By considering some real-world examples, we show that the proposed meta-heuristic provides very accurate results, and still runs 600-2800 times faster than the optimal solution obtained from a general purpose mathematical solver [1].展开更多
A novel scheme for image data restoration is proposed in this letter. First, a window- function model is exploited to describe the data loss in images. It can change the restoration problem into deconvolution in trans...A novel scheme for image data restoration is proposed in this letter. First, a window- function model is exploited to describe the data loss in images. It can change the restoration problem into deconvolution in transform-domain. Then, an iterative algorithm is presented to solve the deconvolution. Because the window-function is available to describe arbitrary shape, our algorithm is suitable for restoring irregular segment of data loss, including square-block. Finally, several simulation tests are done and results prove that the algorithm is valid.展开更多
文摘The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterprise data center requires a significant amount of time and human effort. Following a major disruption, the recovery process involves multiple stages, and during each stage, the partially recovered infrastructures can provide limited services to users at some degraded service level. However, how fast and efficiently an enterprise infrastructure can be recovered de- pends on how the recovery mechanism restores the disrupted components, considering the inter-dependencies between services, along with the limitations of expert human operators. The entire problem turns out to be NP- hard and rather complex, and we devise an efficient meta-heuristic to solve the problem. By considering some real-world examples, we show that the proposed meta-heuristic provides very accurate results, and still runs 600-2800 times faster than the optimal solution obtained from a general purpose mathematical solver [1].
基金Supported by the National Natural Science Foundation of China (No.60072012).
文摘A novel scheme for image data restoration is proposed in this letter. First, a window- function model is exploited to describe the data loss in images. It can change the restoration problem into deconvolution in transform-domain. Then, an iterative algorithm is presented to solve the deconvolution. Because the window-function is available to describe arbitrary shape, our algorithm is suitable for restoring irregular segment of data loss, including square-block. Finally, several simulation tests are done and results prove that the algorithm is valid.
