⌕ Поиск по атласу

NIST · ИТ · 02016f3fc286aebaab2f

02016f3fc286aebaab2f · A Power Management Proxy With a New Best-of-N Bloom Filter Design to Reduce False Positives

A Power Management Proxy With a New Best-of-N Bloom Filter Design to Reduce False Positives

Bloom filters are a probabilistic data structure used to evaluate set membership. A group of hash functions are used to map elements into a Bloom filter and to test elements for membership. In this paper, we propose using multiple groups of hash functions

Официальный источник · 2007-04-12

Полные импортированные сведения карточки
{
  "title_en": "A Power Management Proxy With a New Best-of-N Bloom Filter Design to Reduce False Positives",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2007-04-12",
  "date_original": "April 12, 2007",
  "url": "https://www.nist.gov/publications/power-management-proxy-new-best-n-bloom-filter-design-reduce-false-positives-0",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Miguel Jimeno, K Christensen, Allen L. Roginsky",
  "abstract_excerpt_en": "Bloom filters are a probabilistic data structure used to evaluate set membership. A group of hash functions are used to map elements into a Bloom filter and to test elements for membership. In this paper, we propose using multiple groups of hash functions",
  "id": "02016f3fc286aebaab2f",
  "sources": [
    "NIST Publications"
  ],
  "source_records": [
    {
      "title_en": "A Power Management Proxy With a New Best-of-N Bloom Filter Design to Reduce False Positives",
      "designation": "",
      "series": "",
      "status": "",
      "date": "2007-04-12",
      "date_original": "April 12, 2007",
      "url": "https://www.nist.gov/publications/power-management-proxy-new-best-n-bloom-filter-design-reduce-false-positives-0",
      "source": "NIST Publications",
      "display_en": "",
      "authors_en": "Miguel Jimeno, K Christensen, Allen L. Roginsky",
      "abstract_excerpt_en": "Bloom filters are a probabilistic data structure used to evaluate set membership. A group of hash functions are used to map elements into a Bloom filter and to test elements for membership. In this paper, we propose using multiple groups of hash functions"
    }
  ],
  "translation_state": "none",
  "possible_title_matches": 1
}