Bioinformatics is advanced fromin-house computing infrastructure to cloud computing for tackling the vast quantity of biological
data.This advance enables large number of collaborative researches to share theirworks around the world. In view of that, retrieving
biological data over the internet becomes more and more difficult because of the explosive growth and frequent changes. Various
efforts have been made to address the problems of data discovery and delivery in the cloud framework, but most of them suffer
the hindrance by a MapReduce master server to track all available data. In this paper, we propose an alternative approach, called
PRKad, which exploits a Peer-to-Peer (P2P) model to achieve efficient data discovery and delivery. PRKad is a Kademlia-based
implementation with Round-Trip-Time (RTT) as the associated key, and it locates data according to Distributed Hash Table (DHT)
and XOR metric. The simulation results exhibit that our PRKad has the low link latency to retrieve data. As an interdisciplinary
application of P2P computing for bioinformatics, PRKad also provides good scalability for servicing a greater number of users in
dynamic cloud environments.
