Edge-Aware Offloading for Minimizing Bandwidth Costs in Edge Nodes-Cloud Servers Architecture Using Secure Measures

Mobile-based cloud computing (MBCC) has become a paradigm shift that greatly en-hances the computing power of the mobile devices with limited resources by enabling them to access in-the-cloud resources of highly scalable infrastructures at considerable distance. Nevertheless, the constant and unregulated data transfer between mobile customers and remote cloud providers is deep bandwidth expenses, and at the same time, interfere with the overall system performance, address undesirable energy utili-zation, and sensitive information to security weaknesses. These are especially the problem in bandwidth-limited geographical locations or cost-aware enterprise settings in which the network usage is directly translated into expensive operational costs. This paper proposes a hierarchical, edge-aware architecture of the system in an approach to provisioning a holistic optimization of bandwidth usage as long as end-users remain robust in performance, in no less than three-way integration of mobile devices, local-ized, edge, and centralized cloud data centers. In this proposed ecosystem tasks to be offloaded are strictly encrypted and coded before their offloading and preserving sen-sitive user information as well as mathematically minimizing the encoded payload to the minimum. Also, we introduce a new hybrid approach that combines the data com-pression algorithms and game-theory-based optimization of tasks offloading, dynamic synchronization processes, and protocols of secure transmission through the encrypt-ed and encoded task packing. Finally, this study can be used in regards to the basic development of more sustainable, secure, and cost-efficient mobile-cloud systems that are highly essential in the next generation of Internet of Things (IoT) applications in cost-sensitive environments.