Lately there have been interesting changes at both ends of the spectrum of computing power. On one end there has been a boom in mobile computing devices, fueled by fast growing communication networks. On the other end, there has been substantial growth in high-end data centers that offer cheap, on-demand and virtually unlimited computing resources, popularly named Cloud computing. In the backdrop of these advances in computing and the growth of data intensive domains such as social networks, a new class of applications has emerged taking advantage of not only on-demand scalability of computing clouds but also the sophistication of current mobile computing devices.
This class of applications, named cloud-mobile hybrids, are characterized by the need for heavy computations on the back-end but only simple user interfaces on the front-end. An example of this class of applications is an implementation of the Privacy Score algorithm. Privacy score is a numerical indicator of the level of private details exposed by an individual in a social network. This score is a relative measure and requires substantial computations that can be done in parallel. Presenting the score to the user however requires only a simple UI that may be implemented on a mobile device. With the popularity of social networks and micro-blogging services, a vast amount of data is being collected everyday that provides a plethora of opportunities to implement similar types of data and compute intensive applications.
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