Joint optimization method for task scheduling time and energy consumption in mobile cloud computing environment

TL;DR: A novel service orchestration and data aggregation framework (SODA) is proposed, which can orchestrate data as services and aggregate data packets to reduce data redundancy and service response delay.

TL;DR: This review discusses how clustering methods and optimization techniques are widely applied in energy management due to their capacity to provide solutions for energy consumption reduction, and how machine learning methods such as deep neural network, random forest, and support vector machine are applied to the prediction of energy consumption in the cloud, showing an accurate performance.

TL;DR: This work provides a holistic overview of MCC/MEC technology that includes the background and evolution of remote computation technologies, and surveys up-to-date research on the concepts of offloading mechanisms, offloading granularities, and computational offloading techniques.

TL;DR: An efficient priority and relative distance (EPRD) algorithm to minimize the task scheduling length for precedence constrained workflow applications without violating the end-to-end deadline constraint is proposed.

TL;DR: MAUI supports fine-grained code offload to maximize energy savings with minimal burden on the programmer, and decides at run-time which methods should be remotely executed, driven by an optimization engine that achieves the best energy savings possible under the mobile device's current connectivity constrains.

TL;DR: This paper provides an extensive survey of mobile cloud computing research, while highlighting the specific concerns in mobile cloud Computing, and presents a taxonomy based on the key issues in this area, and discusses the different approaches taken to tackle these issues.

TL;DR: The cloud heralds a new era of computing where application services are provided through the Internet, but is it the ultimate solution for extending such systems' battery lifetimes?

TL;DR: This paper proposes ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images.