Sustainable Offloading in Mobile Cloud Computing: Algorithmic Design and Implementation

Mobile Cloud Computing (MCC) has been extensively explored to be applied as a vital tool to enhance the capabilities of mobile devices, increasing computing power, expanding storage capacity, and prolonging battery life. Offloading works as the fundamental feature that enables MCC to relieve task load and extend data storage through an accessible cloud resource pool. Several initiatives have drawn attention to delivering MCC-supported energy-oriented offloading as a method to cope with a lately steep increase in the number of rich mobile applications and the enduring limitations of battery technologies. However, MCC offloading relieves only the burden of energy consumption of mobile devices; performance concerns about Cloud resources, in most cases, are not considered when dynamically allocating them for dealing with mobile tasks. The application context of MCC, encompassing urban computing, aggravates the situation with very large-scale scenarios, posing as a challenge for achieving greener solutions in the scope of Cloud resources. Thus, this article gathers and analyzes recent energy-aware offloading protocols and architectures, as well as scheduling and balancing algorithms employed toward Cloud green computing. This survey provides a comparison among system architectures by identifying their most notable advantages and disadvantages. The existing enabling frameworks are categorized and compared based on the stage of the task offloading process and resource management types, describing current open challenges and future research directions.