Agile Disk Replacement Strategy for Data Cloud Environment Using Evolutionary Algorithms

Information Technology has become a key differentiator for companies and plays an increasingly critical role within corporations at the same time it commands significant resources and growing respect. Across different types and size of business, the overall dependency on technology is rising. Moreover, due to recent economic turbulence IT spending has come under scrutiny and enterprises are more prudent than before to cut costs. Consequently the cut downs are not only related to macroeconomic parameters, but they influence routine activities like maintenance and hardware replacement in a more direct way. This feature is undesirable for the system administrator/investor but it is also unavoidable. The best that one can do is to try to reduce this uncertainty. Disk failure Prediction (or Forecasting) is one of the instruments in this process. However they are not pragmatic to satiate the needs of today´s enterprise. Given the fundamental financial and price information of power consumption by a particular disk along with its shelf life, we attempt to use Genetic Algorithm to identify disks which if replaced are likely to outperform and at the same time ensuring savings.