TY - CHAP
T1 - A flexible workload generator for simulating stream computing systems
AU - Ajwani, Deepak
AU - Ali, Shoukat
AU - Katrinis, Kostas
AU - Li, Cheng Hong
AU - Park, Alfred J.
AU - Morrison, John P.
AU - Schenfeld, Eugen
PY - 2011
Y1 - 2011
N2 - Stream computing is an emerging computational model for performing complex operations on and across multi-source, high volume data ?ows. Given that the deployment of the model has only started, the pool of mature applications employing this model is fairly small, and therefore the availability of workloads for various types of applications is scarce. Thus, there is a need for synthetic generation of large-scale workloads for evaluation of stream computing applications at scale. This paper presents a framework for producing synthetic workloads for stream computing systems. Our framework extends known random graph generation concepts with stream computing spe-cific features, providing researchers with realistic input stream graphs and allowing them to focus on system development, optimization and analysis. Serving the goal of covering a disparity of potential applications, the presented framework exhibits high user-controlled configurability. The produced workloads could be used to drive simulations for performance evaluation and for proof-of-concept prototyping of processing, networking and operating system hardware and software.
AB - Stream computing is an emerging computational model for performing complex operations on and across multi-source, high volume data ?ows. Given that the deployment of the model has only started, the pool of mature applications employing this model is fairly small, and therefore the availability of workloads for various types of applications is scarce. Thus, there is a need for synthetic generation of large-scale workloads for evaluation of stream computing applications at scale. This paper presents a framework for producing synthetic workloads for stream computing systems. Our framework extends known random graph generation concepts with stream computing spe-cific features, providing researchers with realistic input stream graphs and allowing them to focus on system development, optimization and analysis. Serving the goal of covering a disparity of potential applications, the presented framework exhibits high user-controlled configurability. The produced workloads could be used to drive simulations for performance evaluation and for proof-of-concept prototyping of processing, networking and operating system hardware and software.
UR - https://www.scopus.com/pages/publications/80053024732
U2 - 10.1109/MASCOTS.2011.54
DO - 10.1109/MASCOTS.2011.54
M3 - Chapter
AN - SCOPUS:80053024732
SN - 9780769544304
T3 - IEEE International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems - Proceedings
SP - 409
EP - 417
BT - Proceedings - 19th Annual IEEE/ACM International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2011
T2 - 19th Annual IEEE/ACM International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2011
Y2 - 25 July 2011 through 27 July 2011
ER -