Summary Representation for Service Discovery Protocols

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Title: Summary Representation for Service Discovery Protocols
Author: Ullanatt, Venugopalan
Advisors: Dr.Injong Rhee, Chair
Dr.George Rouskas, Member
Dr.Wenke Lee, Member
Abstract: Recent advances in technology have led to the widespread deployment of computational resources and network-enabled end-devices. This poses new challenges to network engineers: how to locate a particular service or device out of hundreds of thousands of accessible services and devices. One of the major issues involved is the efficient storage, retrieval and dissemination of information about available services. Well known relational database techniques are not very efficient in these situations because our primary concern is the determination of availability of a service, not the retrieval of data. Also, database techniques involve additional overhead for indexing and query processing. We propose a novel scheme for efficient determination of the availability of services called SRDP(SummaryRepresentation for service Discovery Protocols). SRDP makes use of a sub-string search algorithm based on hashing techniques. For this purpose, service descriptions are treated as strings and queries are treated as sub-strings. Information about each service and its attributes is stored as a 128 bit signature in a hash table. To exploit all bits of the signature, a signature creation scheme using the characteristics of the distribution of characters in English language is employed. For the hash table, a Fibonacci hash based scheme and a CRC hash based scheme using primitive polynomials are tested for their effectiveness as hash functions. Results are presented from tests performed using actual URL data obtained from the Internet. Finally we compare the performance and memory requirements of our scheme with a Bloom-filter based approach. Results show that SRDP executes twice as fast, consumes 80% less memory and still provides false drop probabilities comparable to a Bloom filter based approach.
Date: 2001-08-06
Degree: MS
Discipline: Computer Science

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