Energy-aware collaborative sensing for multiple applications in mobile cloud computing

The ubiquity of mobile devices, tablets, wearables and other smart devices, with ever-more
capable embedded sensors, has accelerated the use of mobile sensing applications. These
applications harness the processed sensor data to offer a more context-aware and
personalized user-experience for purposes including healthcare, entertainment,
environmental monitoring and promoting socialization.
However, the resource limitation of mobile devices creates a significant bottleneck for the
realization of such applications. In this scenario, Mobile Cloud Computing (MCC) is a
promising solution that allows the offload of raw or pre-processed sensed data to the
application logic hosted in the cloud. This research utilizes the scalability and processing
capabilities of MCC to present an intelligent framework that readily supports collaborative
sensing and provides efficient collection of the sensed data, whilst conserving the energy of
the mobile devices and meeting the performance constraints of applications.
The benefits of this collaborative sensing framework include the capability to satisfy
multiple mobile applications with optimal sensing using minimal number of mobile devices,
context-driven reporting of sensed data to the application cloud, and achieving all of this in
an energy efficient manner.

A Collaborative Mobile Sensing Framework using Mobile CloudComputing

The cloud heralds a new era of computing where application services are provided through the Internet. Cloud computing can enhance the computing capability of mobile systems, but is it the ultimate solution for extending such system’s battery lifetimes. Cloud computing1 is a new paradigm in which computing resources such as processing, memory, and storage are not physically present at the user’s location. Instead, a service provider owns and manages these resources, and users access them via the Internet. For example, Amazon Web Services lets users store personal data via its Simple Storage Service (S3) and perform computations on stored data using the Elastic Compute Cloud (EC2). This type of computing provides many advantages for businesses—including low initial capital investment, shorter start-up time for new services, lower maintenance and operation costs, higher utilization through virtualization, and easier disaster recovery—that make cloud computing an attractive option. Reports suggest that there are several benefits in shifting computing from the desktop to the cloud.1, 2. The primary constraints for mobile computing are limited energy and wireless bandwidth. Cloud computing can provide energy savings as a service to mobile users, though it also poses some unique challenges.

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Energy efficient data traffic management in mobile cloud computing

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Energy efficient data traffic management in mobile cloud computing