Distributed Data Structures and Algorithms for Disjoint Sets in Computing Connected Components of Huge Network

A network or graph consists of a set of nodes joined by edges. A set of nodes are form a connected component when every vertex has a path to every other node in the set. The connected components of a network can be computed efficiently using depth-first search or disjoint-sets data structures. The disjoint sets approach has the advantages of easily answering queries whether two nodes are in the same connected component and efficiently maintaining the connected components as new edges are added. For huge network with hundreds of millions or billions of nodes, the disjoint set data structures may be too large to be held in memory by a single processor. To solve this problem, we proposes a scheme to partition, distribute, and manipulate the disjoint set data structures among multiple processors in a computing grid.