TY - GEN
T1 - A semantic impact in decentralized resource discovery mechanism for grid computing environments
AU - Shaikh, Abdul Khalique
AU - Alhashmi, Saadat M.
AU - Parthiban, Rajendran
PY - 2012
Y1 - 2012
N2 - The requirement of semantic technology has been augmented day by day in IT related applications due to various features including interoperability. Effective development and organization of semantic knowledge are essential for maximum throughput in any application. We extend and develop two sub-domain computer resource ontologies and utilize them in a resource discovery process of a Grid computing environment to reduce the job rejection rate. Grid computing aggregates distributed computing resources to execute computationally complex jobs. The selection of resources in a Grid system involves finding and locating resources based on users' requirements. Identifying an appropriate resource selection mechanism for Grid jobs is a major concern because overall performance of a Grid depends on it and it also helps to schedule and allocate resources. We compute semantic similarity threshold values and employ both extended ontolgies in a decentralized resource discovery model of Grid Computing. The simulation is carried out using GridSim and PlanetSim to evaluate the effectiveness of a semantic resource discovery model. The results show improved success probability for complex jobs and reduce communication overheads compared to the non semantic resource discovery model.
AB - The requirement of semantic technology has been augmented day by day in IT related applications due to various features including interoperability. Effective development and organization of semantic knowledge are essential for maximum throughput in any application. We extend and develop two sub-domain computer resource ontologies and utilize them in a resource discovery process of a Grid computing environment to reduce the job rejection rate. Grid computing aggregates distributed computing resources to execute computationally complex jobs. The selection of resources in a Grid system involves finding and locating resources based on users' requirements. Identifying an appropriate resource selection mechanism for Grid jobs is a major concern because overall performance of a Grid depends on it and it also helps to schedule and allocate resources. We compute semantic similarity threshold values and employ both extended ontolgies in a decentralized resource discovery model of Grid Computing. The simulation is carried out using GridSim and PlanetSim to evaluate the effectiveness of a semantic resource discovery model. The results show improved success probability for complex jobs and reduce communication overheads compared to the non semantic resource discovery model.
KW - Grid Computing
KW - Ontology
KW - Resource Discovery
KW - Semantic
UR - http://www.scopus.com/inward/record.url?scp=84866685767&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866685767&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33065-0_22
DO - 10.1007/978-3-642-33065-0_22
M3 - Conference contribution
AN - SCOPUS:84866685767
SN - 9783642330643
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 206
EP - 216
BT - Algorithms and Architectures for Parallel Processing - 12th International Conference, ICA3PP 2012, Proceedings
T2 - 12th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2012
Y2 - 4 September 2012 through 7 September 2012
ER -