A Truthful Optimized Task Scheduling in Cloud Computing with Consideration of user Satisfaction

Abstract

Task provisioning and allocation in the cloud computing is a complex process in the real world environment with the satisfaction of user constraints. Truthful greedy mechanism was used in the earlier work which attempts to select and provide the suitable services to the cloud users and also increases the profit of cloud providers by fixing the payment function for the cloud users at run time. This work lacks from more computational time for computing and deciding the payment function for each service provider. In this work, Hybrid Bee-Particle Swarm Optimization (HBPSO) based resource allocation is introduced which would select the optimal service provider for the user request by satisfying the objectives called the makespan and monetary cost. This methodology can considerably reduce the computational cost.