TY - GEN
T1 - Applying QoS-aware service selection on functionally diverse services
AU - Wagner, Florian
AU - Ishikawa, Fuyuki
AU - Honiden, Shinichi
PY - 2012
Y1 - 2012
N2 - The Service-Oriented Computing (SOC) paradigm envisions the composition of loosely coupled services to build complex applications. Most current selection algorithms assume that all services assigned to a certain task provide exactly the same functionality. However, in realistic settings larger groups of services exist that share the same purpose, yet provide a slightly different interface. Incorporating these services increases the number of potential solutions, but also includes functional invalid configurations, resulting in a sparse solution space. As a consequence, applying naïve heuristic algorithms leads to poor results by reason of the increased probability of local optima. For that purpose, we propose a functionality clustering in order to leverage background knowledge on the compatibility of the services. This enables heuristic algorithms to discover valid workflow configurations in shorter time. We integrate our approach into a genetic algorithm by performing repair operations on invalid genomes. In the evaluation we compare our approach with related heuristic algorithms that use the same guided target function but pick services in a random manner.
AB - The Service-Oriented Computing (SOC) paradigm envisions the composition of loosely coupled services to build complex applications. Most current selection algorithms assume that all services assigned to a certain task provide exactly the same functionality. However, in realistic settings larger groups of services exist that share the same purpose, yet provide a slightly different interface. Incorporating these services increases the number of potential solutions, but also includes functional invalid configurations, resulting in a sparse solution space. As a consequence, applying naïve heuristic algorithms leads to poor results by reason of the increased probability of local optima. For that purpose, we propose a functionality clustering in order to leverage background knowledge on the compatibility of the services. This enables heuristic algorithms to discover valid workflow configurations in shorter time. We integrate our approach into a genetic algorithm by performing repair operations on invalid genomes. In the evaluation we compare our approach with related heuristic algorithms that use the same guided target function but pick services in a random manner.
UR - http://www.scopus.com/inward/record.url?scp=84865478892&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-31875-7_12
DO - 10.1007/978-3-642-31875-7_12
M3 - Conference contribution
AN - SCOPUS:84865478892
SN - 9783642318740
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 100
EP - 113
BT - Service-Oriented Computing, ICSOC 2011 Workshops - ICSOC 2011 International Workshops, WESOA, NFPSLAM-SOC, and Satellite Events, Revised Selected Papers
T2 - 2011 International Conference on Service-Oriented Computing, ICSOC 2011
Y2 - 5 December 2011 through 8 December 2011
ER -