Over the last few decades, the Internet ecosystem has been continuously evolving to meet the demands of its ever-increasing user base. Drastic changes in the Internet infrastructure have improved its capacity and throughput performance, enabling a wealth of new services. For Internet Service Providers (ISPs), anticipating and accommodating the rapidly shifting traffic demands has been a technological, economical, and political challenge. Thus far, this challenge has been met in an "organic" fashion, for the most part, based on unilateral actions of many different players such as ISPs, content providers, public policy makers, international organizations, and large enterprises. This symbiotic relationship among many and often competing change factors has led to a system of enormous complexity that was not a product of well-founded engineering principles. Despite the continuous efforts of the scientific and enterprise communities to discover and to model the Internet, understanding its structure remains a hard challenge. In this thesis, we provide a new perspective on the Internet's evolutionary pat- terns at the Autonomous System (AS) level. While many studies have focused on the mathematical models that express the growth of the AS graph topology as a whole, little research has been performed to correlate this growth with geographic, economic, and political data, as well as related business interests. We divide the Internet to five distinct regions using the well-established Internet registry classification and show that the structural properties and evolutionary patterns differ from region to region. We further analyze the business relationships that dominate each region, as well relationships between regions. Conclusions from our analysis is used to explain global as well as local Internet structure phenomena.