Minimizing User Costs in Multi-Broker Mobile Cloud Computing Networks

Abstract

The success and disruption of cloud computing over the past few years is unparalleled.In order to quickly allocate or reallocate virtual computing as well as storage resources, Infrastructure as a Service (IaaS) providers offer commercially accessible services that enable scaling out or in computing capabilities in response to changing needs.Users can provide new apps using IaaS services without having to manage the supporting infrastructure. In this study, the system takes into account an MCC model in which several brokers allot cloud resources to mobile consumers. The approach is distinguished by a heterogeneous cloud architecture and by the many cloud service providers' pricing models. Both a public cloud and a cloudlet are part of it. A competitive strategy and a compete-then-cooperate approach are investigated by the system as a performance bound. The computer creates a cooperative issue with the restriction that none broker should be required to shell out beyond the dispute price, with the objective of lowering the overall average broker price.  The system uses a mix of the branch and bound paradigm with sophisticated convex relaxation techniques to develop a novel globally optimum solution algorithm to handle the ensuing non-convex cooperative issue.