Techniques for measuring peer-to-peer (p2p) networks

Abstract

Techniques for measuring Peer-To-Peer (P2P) networks are provided. P2P are initially seeded with links to feigned content. As a P2P participant accesses a link, metrics are recorded about the P2P network being used by the participant. The metrics are used to form measurements to compare different P2P networks relative to one another.

1 . A system comprising:
 a machine configured with a Peer-To-Peer (P2P) flooder executing on the machine; and   the machine also configured with a P2P measuring service executing on the machine, the P2P flooder configured to distribute feigned content references to content to P2P participants over P2P networks, each feigned content reference points to the P2P measuring service, when the P2P participants activate the feigned content references the P2P measuring service records metrics from the P2P networks and the P2P participants, the P2P measuring service evaluates the metrics to develop general content preferences that aggregate content preferences over a plurality of P2P participants, the general content preferences being associated with content provided by particular advertisers or content providers.   
     
     
         2 . The system of  claim 1 , wherein the P2P measuring service evaluates the metrics to develop additional profiles and ratings for each of the P2P networks. 
     
     
         3 . The system of  claim 2 , wherein the P2P measuring service is to develop the additional ratings for each P2P network relative to remaining ones of the P2P networks. 
     
     
         4 . The system of  claim 1 , wherein the P2P measuring service is to evaluate the metrics to develop metrics for each of the particular advertisers or content providers. 
     
     
         5 . The system of  claim 1 , wherein the P2P measuring service is to evaluate the metrics to develop a preference for a type of content emerging as a preference in each of the P2P networks. 
     
     
         6 . The system of  claim 1 , wherein the P2P measuring service uses the metrics to establish measurements from each of the P2P networks. 
     
     
         7 . The system of  claim 6 , wherein the P2P measuring service uses measurements to estimate a size for each of the P2P networks relative to the other remaining P2P networks. 
     
     
         8 . The system of  claim 1 , wherein the developed general content preferences are used to perform targeted advertising or customized content selection and delivery based on the general content preferences. 
     
     
         9 . A method comprising:
 receiving, by a machine, attempts to access content from Peer-To- Peer (P2P) participants of a plurality of P2P networks;   gathering, by the machine, metrics from the P2P participants and the P2P networks in response to the attempts; and   evaluating, by the machine, the metrics to develop general content preferences that aggregate content preferences over a plurality of P2P participants, the general content preferences being associated with content provided by particular advertisers or content providers.   
     
     
         10 . The method of  claim 9 , wherein receiving further includes identifying the attempts and requests for content. 
     
     
         11 . The method of  claim 9  further comprising using the metrics and the attempts for the content to develop a preference for a type of content for each of the P2P networks. 
     
     
         12 . The method of  claim 9  further comprising developing ratings for each of the P2P networks relative to one another based on the metrics. 
     
     
         13 . The method of  claim 9  further comprising developing metrics for each of the particular advertisers or content providers. 
     
     
         14 . The method of  claim 9  further comprising developing ratings for each of the particular advertisers or content providers relative to one another based on the metrics. 
     
     
         15 . The method of  claim 9 , wherein the developed general content preferences are used to perform targeted advertising or customized content selection and delivery based on the general content preferences. 
     
     
         16 . A non-transitory computer-readable medium having instructions thereon, the instructions when processed by a machine cause the machine to:
 receive attempts to access content from Peer-To-Peer (P2P) participants of a plurality of P2P networks;   gather metrics from the P2P participants and the P2P networks in response to the attempts; and   evaluate the metrics to develop general content preferences that aggregate content preferences over a plurality of P2P participants, the general content preferences being associated with content provided by particular advertisers or content providers.   
     
     
         17 . The computer-readable medium of  claim 16 , being further configured to identify the attempts and requests for content. 
     
     
         18 . The computer-readable medium of  claim 16 , being further configured to use the metrics and the attempts for the content to develop a preference for a type of content for each of the P2P networks. 
     
     
         19 . The computer-readable medium of  claim 16 , being further configured to develop ratings for each of the P2P networks relative to one another based on the metrics. 
     
     
         20 . The computer-readable medium of  claim 16 , being further configured to develop metrics for each of the particular advertisers or content providers.