Three-tier offloading model for energy-efficient mobile computation. (c2018)

Abstract

Integrating the smart phone in our daily life where many info's and tools can be accessed, is a new horizon for achieving a better quality of life. Accessing and analyzing data at the right time with the right price is the core of human need. We are targeting a professional environment where some complex applications are being developed and used on mobile devices, such as Health Care or Educational Environments. Mobile devices, however, remain short in resources including energy, computation, and storage. Edge computing emerged as an effective solution to enable mobile devices processing complex computations through offloading to geographically close computing servers. While offloading provides access to powerful servers, frequent transmission of tasks over wireless links leads to draining the battery of mobile devices. In this work, we propose two contributions to help in the adaptation of mobile offloading. First, we elaborate a design methodology related to the development of applications in any professional environment targeting energy savings whereby we introduce a concept of adding annotations dynamically in the headers of webpages. Second, we provide a mobile offloading model that makes use of the multiple wireless interfaces of mobile devices to transfer computation tasks to edge servers only when energy savings are expected and delay requirements can be met. We consider two widely available wireless interfaces namely, Wi-Fi and ZigBee, and formulate our problem as integer linear programming to decide whether to offload on any of the existing interfaces or compute locally while minimizing the total energy consumption and meeting time limits. The work presents various results under different system parameters and demonstrate considerable gains in energy consumption.