Disease Motivated Model for Future Dynamic Computing

Abstract

Future computing entities should be capable of accessing computing resources for data-intensive algorithm execution. This should be realizable in operational contexts where internet accessibility to cloud contexts becomes challenging. Such a scenario describes developing contexts. In addition, future computing entities also make use of multiple operating systems in a context where the computing resources are reduced due to the use of partitions. The use of partitions is recognized to reduce the number of accessible computing resources and increase the overhead associated with computing resource allocation. The presented research proposes an architecture where an operating system is logically stowed and selectively activated without involving the use of partition. This frees up the number of computing resources previously locked in different partition systems and reduces the computing resource overhead. Analysis shows that the proposed framework increases the accessible computing resources by 14.6% on average. In addition, the computing resource overhead is reduced by 21 % on average.