WebParF: A Web partitioning framework for Parallel Crawlers
This addresses the challenge of scaling web crawling for large-scale WWW exploration using parallel processing, though it appears incremental in the field of parallel crawlers.
The paper tackles the problem of efficiently distributing URLs among parallel crawlers to improve web crawling performance, proposing the WebParF framework that partitions the URL frontier into multiple queues while addressing design challenges.
With the ever proliferating size and scale of the WWW [1] efficient ways of exploring content are of increasing importance. How can we efficiently retrieve information from it through crawling? And in this era of tera and multi-core processors, we ought to think of multi-threaded processes as a serving solution. So, even better how can we improve the crawling performance by using parallel crawlers that work independently? The paper devotes to the fundamental development in the field of parallel crawlers [4] highlighting the advantages and challenges arising from its design. The paper also focuses on the aspect of URL distribution among the various parallel crawling processes or threads and ordering the URLs within each distributed set of URLs. How to distribute URLs from the URL frontier to the various concurrently executing crawling process threads is an orthogonal problem. The paper provides a solution to the problem by designing a framework WebParF that partitions the URL frontier into a several URL queues while considering the various design issues.