Efficient Resource Allocation for Crowd-Cloud Assisted D2D Computation Offloading

The emergence of innovative technologies for mobile devices has enabled us to crowdsource large scale tasks to these devices. This gives rise to a new paradigm where mobile clouds can be accessed by an end user for data storage and processing over a wireless connection. A crowd-cloud system consists of a central Consumer Crowd Interface and several crowd-clouds. Each crowd-cloud comprises of mobile devices which can perform computations and storage tasks allotted to them. This paper presents a mathematical formulation of the total energy consumption in such a system including energy for offloading, computation and downloading of tasks to and from mobile devices. The optimization problem is solved using Lagrangian dual-decomposition approach.