PROPOSED NEW SECURE HYBRID MOBILE CLOUD COMPUTING TO IMPROVE POWER AND DELAY

Abstract

Systems for large-scale distributed computing, such as cloud and mobile cloud deployments, offer wonderful services that boost both individual and institutional productivity. To meet performance requirements, cloud computing takes on the risks associated with P2P computing and introduces P2P cloud systems as an add-on to the federated cloud. These cloud deployments can handle resource provisioning at a very cheap cost because of their decentralized architecture, which is built on independent nodes and resources without any specific central control and monitoring. As a result, many mobile apps and services are prepared to easily scale to a massive user base. Among them, data-driven apps have proven to be the most popular and profitable. However, data-rich applications present additional challenges, such as storage, big data processing, and the critically important responsibility of preserving private or sensitive data. In this article, we first survey existing multi-tiered cloud architectures and then propose a method for dealing with large amounts of data. Second, we investigate P2P Cloud Systems (P2PCS) for processing and analyzing large datasets. Third, using healthcare systems as a case study, we propose a hybrid mobile cloud computing approach based on the cloudlets notion. The model is then tested in a simulated environment using the Mobile Cloud Computing Simulator (MCCSIM). The experimental result shows power and delay improve by 75% in a proposed cloud model. Finally, we strengthen our suggestions by outlining and discussing potential security and privacy countermeasures.