A Cost and Contention Conscious Scheduling for Recovery in Cloud Environment

Cloud Computing (CC) model plays an important role for the growth of contemporary IT industry where stability, availability and partition tolerance of computational resources mean a great deal. It is of utmost significance that not only cloud services are to be provided with satisfactory performance but also they are able to minimize and resiliently recover from potential damages when cloud infrastructures are subject to changes and/or disasters. This study discusses a method that results in potentially better resiliency and faster recovery from failures based on the well-known genetic algorithm. Moreover, we aim to achieve a globally optimized performance as well as a service solution that can remain financially and operationally balanced according to customer preferences. The proposed methodology has undergone various and intensive evaluations to be proclaimed of their effectiveness and efficiency, even when put under tight comparison with other existing work of relevant aspects.