Mobile P2P Fast Similarity Search

Bocek, Thomas; Hecht, Fabio; Hausheer, David; Hunt, Ela; Stiller, Burkhard

doi:10.1109/ccnc.2009.4785013

Cited by 1 publication

(5 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FastSS [6] performs a similarity search using the edit distance metric and is faster than DP. However, the data has to be indexed beforehand.…”

Section: A Similarity Search Algorithmsmentioning

confidence: 99%

“…Apart from P2PFastSS, a P2P search based on the edit distance can be built using concepts presented in Ahmed et al, Karnstedt et al, and Aekaterinidis et al However, the later two approaches do not work efficiently with small words in distributed systems, as pointed out by [12] and studied by [6] in centralized systems. The first approach has defined its own routing based on Bloom filters.…”

Section: Dcomparison With Other Approachesmentioning

confidence: 99%

“…The result contains a document ID and the keyword. For a given k, neighbors with an edit distance k or larger (up to 2k) are found [6]. Before the document is retrieved using get(key), potential matches are confirmed using DP (see Section II) to check if they do not exceed the given edit distance (cf.…”

Section: B Searching (Second Phase)mentioning

confidence: 99%

“…Neighborhood generation based on deletions has complexity , where m is the length of a word and k is the edit distance [6]. As P2PFastSS uses a deletion neighborhood, a factor of is considered during searching and indexing.…”

Section: Theoretical Analysismentioning

confidence: 99%

“…For example, if k=2, the overhead would increase by a factor [6]. For language-based texts, m is constant.…”

Section: Implementation and Experimental Evaluationmentioning

confidence: 99%

See 4 more Smart Citations

Fast similarity search in peer-to-peer networks

Bocek

Hunt

Hausheer

et al. 2008

NOMS 2008 - 2008 IEEE Network Operations and Management Symposium

Self Cite

View full text Add to dashboard Cite

Peer-to-peer (P2P) systems show numerous advantages over centralized systems, such as load balancing, scalability, and fault tolerance, and they require certain functionality, such as search, repair, and message and data transfer. In particular, structured P2P networks perform an exact search in logarithmic time proportional to the number of peers. However, keyword similarity search in a structured P2P network remains a challenge. Similarity search for service discovery can significantly improve service management in a distributed environment. As services are often described informally in text form, keyword similarity search can find the required services or data items more reliably. This paper presents a fast similarity search algorithm for structured P2P systems. The new algorithm, called P2P fast similarity search (P2PFastSS), finds similar keys in any distributed hash table (DHT) using the edit distance metric, and is independent of the underlying P2P routing algorithm. Performance analysis shows that P2PFastSS carries out a similarity search in time proportional to the logarithm of the number of peers. Simulations on PlanetLab confirm these results and show that a similarity search with 34,000 peers performs in less than three seconds on average. Thus, P2PFastSS is suitable for similarity search in large-scale network infrastructures, such as service description matching in service discovery or searching for similar terms in P2P storage networks. Abstract-Peer-to-peer (P2P) systems show numerous advantages over centralized systems, such as load balancing, scalability, and fault tolerance, and they require certain functionality, such as search, repair, and message and data transfer. In particular, structured P2P networks perform an exact search in logarithmic time proportional to the number of peers. However, keyword similarity search in a structured P2P network remains a challenge. Similarity search for service discovery can significantly improve service management in a distributed environment. As services are often described informally in text form, keyword similarity search can find the required services or data items more reliably. This paper presents a fast similarity search algorithm for structured P2P systems. The new algorithm, called P2P Fast Similarity Search (P2PFastSS), finds similar keys in any distributed hash table (DHT) using the edit distance metric, and is independent of the underlying P2P routing algorithm. Performance analysis shows that P2PFastSS carries out a similarity search in time proportional to the logarithm of the number of peers. Simulations on PlanetLab confirm these results and show that a similarity search with 34,000 peers performs in less than three seconds on average. Thus, P2PFastSS is suitable for similarity search in large-scale network infrastructures, such as service description matching in service discovery or searching for similar terms in P2P storage networks.

show abstract

“…FastSS [6] performs a similarity search using the edit distance metric and is faster than DP. However, the data has to be indexed beforehand.…”

Section: A Similarity Search Algorithmsmentioning

confidence: 99%

Section: Dcomparison With Other Approachesmentioning

confidence: 99%

Section: B Searching (Second Phase)mentioning

confidence: 99%

Section: Theoretical Analysismentioning

confidence: 99%

“…For example, if k=2, the overhead would increase by a factor [6]. For language-based texts, m is constant.…”

Section: Implementation and Experimental Evaluationmentioning