Hybrid cloud to save battery life

Romanian computer scientists have developed a new system that is said to boost phone battery life by booting power-consuming computational tasks to an on-the-fly ad hoc cloud in which smartphones are both clients and computing resources.

The new system, called ‘hybrid contextual cloud in ubiquitous platforms comprising of smart phones’, or HYCCUPS for short, will be discussed in a forthcoming research paper in the International Journal of Intelligent Systems Technologies and Applications.

Radu-Corneliu Marin of the University Politehnica of Bucharest explains how the advent of the smartphone gives almost everyone a very powerful computer for communications, watching and editing videos, taking photographs, browsing the web and even making phone calls. However, this leads to a significant increase in power consumption. This means that users who switch from older phones that lasted a week on a single charge are soon frustrated by how quickly the battery drains on their new device, usually in a matter of hours rather than days if it is used intensively.

Much of the computational activity used by a smartphone to carry out various tasks could be offloaded to other mobile devices, just as it now often is with a desktop or laptop computer. The device itself then becomes an interface to applications running on other phones ‘in the cloud’ and simply uploads raw data and downloads the processed material as and when it is needed. As more and more functionality can be ported to the cloud in this way, so the central processing unit (CPU) of the device requires less power, which means longer battery life.

HYCCUPS is middleware - software that sits between the end-user device, the smartphone in this case, and the mobile cloud. The system creates a hybrid cloud allowing smartphones to schedule and offload process execution to other resources and so reduce energy consumption to save battery life. The scheduling process itself is assisted by a contextual search technology that works behind the scenes without user intervention to predict the availability and mobility of mobile resources - such as other smartphones on a user’s high-speed wireless, Wi-Fi network - so that the whole power-saving process can be optimised without loss of service or slowing down applications.