analyzing the impact of churn and malicious behavior on the quality of peer-to-peer web search
In an attempt to increase the spectrum of searchable information while attenuating scalability issues, Peer-to-Peer (P2P) networks have been viewed as an alternative way to design new Web search engines. However, the effectiveness of P2P Web searching may be severely limited by characteristics commonly observed in real P2P systems such as peer churn and malicious behavioral patterns. This paper analyzes the impact of each such issue on the effectiveness of P2P Web searching. In order to estimate boundaries, we focus our analysis on P2P network models with very high and low levels of peer collaboration. Our findings reveal that such patterns could strongly affect the effectiveness of P2P Web searching. In networks with a high level of peer collaboration, a significant fraction of queries suffer an impact on the quality of search of at least 24\% and 26\% even in slightly insecure and unstable scenarios. We also confirm that the impact of each such issue in real-world, less collaborative networks can be even more intense (73\% and 75\%). Thus, together with the high autonomy of peers and the absence of file-sharing benefits in replicating documents into the network, we argue that effectiveness of P2P Web search engines would strongly depend on new, application-specific reputation and incentive mechanisms.
churn malicious behavior web search engines peer-to-peer systems