A distributed randomized approach for the PageRank computation: Part 1

In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the obtained results. The algorithm quantifies the importance of each Web page based on the link structure of the Web. In this two-part paper, we first provide an overview of the original problem setup. Then, we propose several distributed randomized schemes for the computation of the PageRank, where the pages can locally update their values by communicating to those connected by links. A detailed discussion on the close relations to the multi-agent consensus problems is also given.