Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In peer-to-peer (P2P) networks, reputation aggregation and ranking are the most time-consuming and space-demanding operations.  proposes a new gossip protocol for fast score aggregation.  developed a Bloom filter architecture for efficient score ranking. These techniques do not require any secure hashing or fast lookup mechanism, thus are applicable to both unstructured and structured P2P networks.  report the design principles and performance results of a simulated GossipTrust reputation system. Randomized gossiping with effective use of por nodes enables light-ight aggregation and fast dissemination of global scores in O(log 2  n) time steps, where n is the P2P network size. The Gossip-based protocol is designed to tolerate dynamic peer joining and departure, as ll as to avoid possible peer collusions. The scheme has a considerably low gossiping message overhead, i.e. O(n log 2  n) messages for n nodes. Bloom filters demand at most 512 KB memory per node for a 10,000-node network.  evaluate the performance of GossipTrust with distributed P2P file-sharing and parameter-seping applications. The simulation results demonstrate that GossipTrust has small aggregation time, low memory demand, and high ranking accuracy. These results suggest promising advantages of using the GossipTrust system for trusted P2P applications.
['Runfang Zhou', 'Kai Hwang', 'Min Cai']
I am writing a research paper on a idea GossipTrust for Fast Reputation Aggregation in Peer-to-Peer Networks
[{"from": "human", "value": "I am writing a research paper on a idea GossipTrust for Fast Reputation Aggregation in Peer-to-Peer Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In peer-to-peer (P2P) networks, reputation aggregation and ranking are the most time-consuming and space-demanding operations.  proposes a new gossip protocol for fast score aggregation.  developed a Bloom filter architecture for efficient score ranking. These techniques do not require any secure hashing or fast lookup mechanism, thus are applicable to both unstructured and structured P2P networks.  report the design principles and performance results of a simulated GossipTrust reputation system. Randomized gossiping with effective use of por nodes enables light-ight aggregation and fast dissemination of global scores in O(log 2  n) time steps, where n is the P2P network size. The Gossip-based protocol is designed to tolerate dynamic peer joining and departure, as ll as to avoid possible peer collusions. The scheme has a considerably low gossiping message overhead, i.e. O(n log 2  n) messages for n nodes. Bloom filters demand at most 512 KB memory per node for a 10,000-node network.  evaluate the performance of GossipTrust with distributed P2P file-sharing and parameter-seping applications. The simulation results demonstrate that GossipTrust has small aggregation time, low memory demand, and high ranking accuracy. These results suggest promising advantages of using the GossipTrust system for trusted P2P applications."}]