Mobile traffic sampling and peer routing schemes for location-sensitive and resource-efficient wireless services

Abstract

Most of the ideas for the work in this dissertation came about when, back when I was still working for mobile wireless carriers, there was a growing demand for a value added service that was compatible, scalable, but above all, personal. Most available solutions provide one, or in some cases two, but not all three aspects in one offering. This work is an attempt to bridge that paradigm. Why the focus on location-sensitive services? In today's increasingly connected world, we are constantly exposed to an increasing amount of noise in our digital consumption, which ultimately detracts us from our primary reasons to interact with the digital space. Our intentions are all about relevancy. Location is one of the primary enablers for relevancy - why indeed do consumers and businesses consider more relevant what is immediately in their vicinity - and also one of the key drivers of next generation cost and energy- efficient services, as we shall see in this work. Whilst there have been many attempts to address this need, one of the major failures has been in the delivery of such an enabler, owing mainly to the challenges presented by the underlying infrastructures. A resource-efficient, scalable model of peer networking can address this challenge, and the underlying algorithms as presented can be applied to a variety of other challenges, as will be shown in further detail. I believe in a world where location, personalization, and efficient delivery will herald a golden era of relevancy, and this work is my contribution to that vision.