A genetic
Dipankar Dutta, R. C. Joshi · 2011
The complex business strategies of cloud services make Job scheduling a challenging issue. The mapping of user jobs onto a computing resource to achieve maximum benefit, satisfying the varying QoS of user's jobs, is the ultimate goal of a cloud provider. As this scheduling problem belongs to the family of combinatorial problems, it cannot be formulated as a linear programming problem and any simple rule or algorithm cannot achieve the optimal solution in finite time. In this paper, a genetic algorithm approach to cost based multi QoS job scheduling has been proposed. A model for cloud computing environment has been also proposed and some popular genetic cross over operators, like PMX, OX, CX and mutation operators, swap and insertion mutation are used to produce a better schedule. The algorithm guarantees the best solution in finite time.