DYNA-RANK: Efficient Calculation and Updation of PageRank

Abstract

The decision of the ranking of web page is very important in web, as its growing and changing very rapidly. Ranking of the results in a search engine for a query plays crucial role for huge database like Web, where one query can have millions of results. The browsing nature of web will mostly depend on the ranking of the search results. The existing approaches for calculating pagerank values are mostly centralized and the ones which are distributed, are not being used for practical purposes because of the scalability reasons. The centralized approaches considers total web as one graph and they calculate the pagerank values of total graph after certain time period, which takes long execution time and can be in days. In the same way updating the graph also compels to recalculate all the pagerank values of all the pages in the graph. This suggests possible applicability of the distributed algorithm to pagerank computations as a replacement for the centralized pagerank calculation algorithm. Considering the importance of the "Ranking" in searching context, our approach DYNA-RANK, focuses upon efficiently calculating and updating Google's pagerank vector using "peer to peer" system. The changes in the web structure will be handled incrementally amongst the peers. DYNA-RANK produces the relative pagerank on each peer. DYNA-RANK is proven to take less computation time and less number of iterations compared to centralized approach.