2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation (2012)
July 15, 2012 to July 19, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PADS.2012.11
The cloud computing paradigm attracts increasing amount of Modeling&Simulation (M&S) practitioners to perform their simulations in the cloud. Two issues, namely, the architecture of the Cloud-based Simulation (CSim) and the parallel simulation job scheduling in the CSim, should be addressed ï¬rst to make the CSim practical. This paper reports our recent work on the two issues. The architecture we proposed covers the software involved in the whole process of M&S by providing the Modeling as a Service (MaaS), the Execution as a Service (EaaS) and the Analysis as a Service (AaaS). The architecture also encourages the reuse of available simulation resources with the aid of the Simulation Resource as a Service (SRaaS). For the issue of parallel simulation job scheduling in the CSim, we ï¬rst propose a two-tier processor partition method to organize virtual machines (VMs) for parallel simulation workload consolidation, the two-tier VMs have different CPU priority. We then present four scheduling algorithms under such a partition method to cope with four common situations. Our extensive experiments on well-known traces show that all the four algorithms signiï¬cantly outperform their competitors.
Computational modeling, Scheduling, Cloud computing, Scheduling algorithms, Computer architecture, Resource Consolidation, M&S, Cloud Computing, Simulation as a Service, Parallel Job scheduling
Xiaocheng Liu, Xiaogang Qiu, Bin Chen, Kedi Huang, "Cloud-Based Simulation: The State-of-the-Art Computer Simulation Paradigm", 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation, vol. 00, no. , pp. 71-74, 2012, doi:10.1109/PADS.2012.11