{"doi":"10.1109/lcn.2008.4664213","title":"P2P directory search: Signature Array Hash Table","abstract":null,"journal":"2008 33rd IEEE Conference on Local Computer Networks (LCN)","year":2008,"id":632868,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":623185,"name":"Ken Christensen","orcid":"0000-0002-3736-5500","position":1,"is_corresponding":false},{"id":1640609,"name":"Miguel Jimeno","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"P2P directory search: Signature Array Hash Table","abstract":"Bloom filters are a well known data structure for approximate set membership. Bloom filters are space efficient but require many independent hashes and consecutive memory accesses for an element test. In this paper, we develop a hash table data structure that stores string signatures in an array. This new signature array hash table (SAHT) supports faster element testing than a bloom filter and requires less memory than a standard hash table that uses linked-list chains. The SAHT also supports removal of elements (which a Bloom filter does not) and addition of elements at the expense of requiring about 1.5x more memory than a bloom filter with same false positive rate.","is_dataset_classified":null,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19767382","pmcid":null,"openalex_id":"https://openalex.org/W2129541134","authors":[],"funders":[],"total_grants":0,"fwci":0.5092,"citation_percentile":0.5891264,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx5/4656373/4664131/04664213.pdf?arnumber=4664213","host_type":"publisher"},{"url":"https://doi.org/10.1109/lcn.2008.4664213","host_type":""},{"url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.42","host_type":""}],"fields_of_study":["Caching and Content Delivery","Peer-to-Peer Network Technologies","Opportunistic and Delay-Tolerant Networks"],"mesh_terms":[],"keywords":["Bloom filter","Hash function","Computer science","Hash table","Data structure","Hash tree","Signature (topology)","Hash chain","Dynamic perfect hashing","Linear hashing","Double hashing","Rolling hash","Filter (signal processing)","Algorithm","Theoretical computer science","Mathematics","Operating system"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T10:28:54.782556Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}