Service task partition and distribution in star topology computer grid subject to data security constraints

• Published in: Reliability engineering & system safety Vol. 96; no. 11; pp. 1507 - 1514
• Main Authors: Xiang, Yanping, Levitin, Gregory
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2011; Elsevier
• Subjects: Algorithms; Applied sciences; Computer information security; Computer networks; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Data security; Distributed processing; Evolutionary; Exact sciences and technology; Grid system; Memory and file management (including protection and security); Memory organisation. Data processing; Operational research and scientific management; Operational research. Management science; Optimization; Partitions; Reliability theory. Replacement problems; Service reliability; Service time; Software; Subtask distribution; Tasks; Universal generating function; Service time; SDTG; Data security; Grid system; Subtask distribution; u-function; pmf; RMS; Universal generating function; UA; Service reliability; EB; Service life; High performance; Partition; Parallel algorithm; Dependability; Evolutionary algorithm; Resource allocation; Grid; State space; Distributed system; Topology; Distributed computing; Optimization; Problem solving; Reliability; Service quality; Computer security; Mathematical programming
• DOI: 10.1016/j.ress.2011.06.013
• ISSN: 0951-8320

The paper considers grid computing systems in which the resource management systems (RMS) can divide service tasks into execution blocks (EBs) and send these blocks to different resources. In order to provide a desired level of service reliability the RMS can assign the same blocks to several independent resources for parallel execution. The data security is a crucial issue in distributed computing that affects the execution policy. By the optimal service task partition into the EBs and their distribution among resources, one can achieve the greatest possible service reliability and/or expected performance subject to data security constraints. The paper suggests an algorithm for solving this optimization problem. The algorithm is based on the universal generating function technique and on the evolutionary optimization approach. Illustrative examples are presented. ► Grid service with star topology is considered. ► An algorithm for evaluating service reliability and data security is presented. ► A tradeoff between the service reliability and data security is analyzed. ► A procedure for optimal service task partition and distribution is suggested.