Evolution of Networks: From Biological Nets to the Internet and WWW ,
If a single word could capture the new concepts dominating life at the beginning of the 21st century, a strong candidate would be “connectivity.” Indeed, as we witness the development of crucial interdependencies in technology, information organization, and social life, we see that links and networks are ever present. Previously unconnected computers and devices are linked via the internet; formerly scattered information is reorganized in consolidated databases; geographically fragmented groups of people with common interests are brought together in virtual communities. Moreover, we increasingly recognize that networking is not a human invention, but represents an organizational form that nature has exploited for millions of years, on scales from cells to ecosystems.
The important role networks play in many areas of scientific inquiry creates the need for a conceptual framework that captures the structure and behavior of interconnected systems. For more than 40 years, the modeling of complex networks was dominated by the random-network paradigm, which assumes that nodes are connected randomly to each other. In the late 1990s, the internet revolution offered access to a series of databases that, in the hands of network researchers, produced spectacular maps of the World Wide Web, the cell, and scientific-collaboration networks.
Measurements performed on such large maps offered the first indication that the random-network paradigm does not apply to real networks. What does apply is a rigid architecture that can be understood in terms of a few simple organizing principles. One of the most surprising developments was the discovery that many real networks are scale free. That is to say, most nodes have only a few links and the network is held together by a few highly connected hubs. Those hubs have a fundamental impact on just about all properties of complex systems, from their robustness against node failures and attack to, for example, the way viruses spread.
Evolution of Networks: From Biological Nets to the Internet and WWW, as the first monograph to offer a coherent and balanced description of the key results of network theory, serves as a readable introduction to the field. It is a very ambitious undertaking that acts as textbook and handbook and that succeeds well at both. Network research is not a purely theoretical undertaking: One needs to collect data with the purpose of mapping real systems, analyze the obtained network’s topology, model the observed features, and develop analytical approaches to solve the proposed model. The book does a great job of introducing the reader to each of those phases and offers a step-by-step guide on how to move from measurement to modeling, and how to then exploit the strength of an analytical solution.
Dorogovtsev and Mendes, who have made a series of fundamental contributions to the field, handle their material with the confidence of experts. They are at home with mapping and measurement issues, but their strength is in addressing the mathematical challenges that arise when one attempts to model evolving networks. A wide range of illustrations, from explanatory sketches to diagrams, helps the reader navigate through the material. Network research is a highly visual science, and network representations often have a visual appeal that borders on art. Not to have any of those great colorful images in the book is a loss.
The finding that most networks—from the man-made internet to the evolution-directed cell—are shaped by the same laws has turned network research into a truly interdisciplinary enterprise. And the results of network theory are no longer hidden in journals for mathematics, computer science, or physics, but are discussed in papers covering a wide variety of disciplines and regularly featured in books written for a general audience. The novelty and fundamental nature of the advances in network theory have paid off with the emergence of a vibrant, rapidly growing, and highly competitive community focused on complex networks. The tools and ideas developed in the past few years are now used by more than a dozen companies with social networks as the basis for their business model and have initiated close to a thousand research articles. This growth in interest has created the need for authoritative and pedagogical introductions like Evolution of Networks that can lower the barriers for newcomers.
Given the rapid progress in network theory, no book or review article is going to stay fresh. Since Dorogovtsev and Mendes’s book was published, theorists have witnessed several major advances, from an understanding of just how important the hierarchical nature of complex networks is, to the role of subgraphs and motifs. Yet those advances emphasize just how valuable the book is: Evolution of Networks offers an excellent foundation from which the fast-paced field can be approached with confidence. It would be an excellent addition to the bookshelf of anyone interested in networks.
