Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Search and replication in unstructured peer-to-peer networks
ICS '02 Proceedings of the 16th international conference on Supercomputing
A local search mechanism for peer-to-peer networks
Proceedings of the eleventh international conference on Information and knowledge management
Improving Search in Peer-to-Peer Networks
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and
Tapestry: An Infrastructure for Fault-tolerant Wide-area Location and
Probabilistic file indexing and searching in unstructured peer-to-peer networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Improve Searching by Reinforcement Learning in Unstructured P2Ps
ICDCSW '06 Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems
Survey of research towards robust peer-to-peer networks: search methods
Computer Networks: The International Journal of Computer and Telecommunications Networking
Distributed caching in unstructured peer-to-peer file sharing networks
Computers and Electrical Engineering
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Searching for particular resources in a large-scale decentralized unstructured network can be very difficult since there is no centralized management to provide the specific location of resources. Moreover, the dynamic behavior of networks and the diversity of user behavior cause the search more complex and may not guarantee success. To address the problems, we propose a new adaptive resource indexing technique that aims to increase both efficiency and quality of the search by reducing both messages and time required for each query. Our approach consists of two complementary techniques. One is an index selection technique that selectively keeps the indices at each peer to increase the chance of successful queries with minimum space requirement. Another is an index distribution technique that automatically adjusts index distribution rate based on the search performance to optimize both the search performance and overhead. We simulate the technique in various network conditions and the results show that our technique is effective in decreasing hop counts and messages needed for resolving queries with only small overhead. It decreases the average hop count by up to 44% with 75%-less messages when used with flooding based queries even facing high churn. Furthermore, the query success rate with a limited timeout condition also increases, approaching nearly to 100%.