Abstract
Efficient content location is a fundamental problem for decentralized peer-to-peer systems. Gnutella, a popular file-sharing application, relies on flooding queries to all peers. Although flooding is simple and robust, it is not scalable. In this chapter, we explore how to retain the simplicity of Gnutella while addressing its inherent weakness: scalability. We propose two complementary content location solutions that exploit locality to improve scalability. First, we look at temporal locality and find that the popularity of search strings follows a Zipf-like distribution. Caching query results to exploit temporal locality can significantly decrease the amount of traffic seen on the network by 3-times while using only a few megabytes of memory. As our second solution, we exploit a simple, yet powerful principle called interest-based locality, which posits that if a peer has a particular piece of content that one is interested in, it is very likely that it will have other items that one is interested in as well. We propose that peers loosely organize themselves into an interest-based structure on top of the existing Gnutella network. When using our algorithm, called interest-based shortcuts, a significant amount of flooding can be avoided, reducing the total load in the system by a factor of 3 to 7 and reducing the time to locate content to only one peer-to-peer hop. We demonstrate the existence of both types of locality and evaluate our solutions using traces of several different content distribution systems such as the Web and popular peer-to-peer file-sharing applications.
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Sripanidkulchai, K., Zhang, H. (2005). Content Location in Peer-to-Peer Systems: Exploiting Locality. In: Tang, X., Xu, J., Chanson, S.T. (eds) Web Content Delivery. Web Information Systems Engineering and Internet Technologies Book Series, vol 2. Springer, Boston, MA. https://doi.org/10.1007/0-387-27727-7_4
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DOI: https://doi.org/10.1007/0-387-27727-7_4
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