TY - GEN
T1 - Bounding aggregations on phase-type arrivals for performance analysis of clouds
AU - Aït-Salaht, Farah
AU - Castel-Taleb, Hind
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/5
Y1 - 2016/12/5
N2 - We evaluate the performance of a cloud system using ahysteresis queueing system with phase-type and batch arrivals. To represent the dynamic allocation of the resources, the hysteresis queueactivates and deactivates the virtual machines according to the threshold values of the queue length. We suppose a variable traffic intensity as the client requests (or jobs) arrive by batches, and follow a phase-type process. This system is represented by a complex Markov chain which is difficult to analyze, especially when the size of the state space increases and the length of batch arrival distribution is large. So, to solve this problem, we propose to use stochastic bounds and define bounding systems less complex. We give some results for the performance measures and compare the proposed bounding models with the exact one. The relevance of our methodology is to offer a trade-off betweencomputational complexity and accuracy of the results and provide very interesting solutions for network dimensioning.
AB - We evaluate the performance of a cloud system using ahysteresis queueing system with phase-type and batch arrivals. To represent the dynamic allocation of the resources, the hysteresis queueactivates and deactivates the virtual machines according to the threshold values of the queue length. We suppose a variable traffic intensity as the client requests (or jobs) arrive by batches, and follow a phase-type process. This system is represented by a complex Markov chain which is difficult to analyze, especially when the size of the state space increases and the length of batch arrival distribution is large. So, to solve this problem, we propose to use stochastic bounds and define bounding systems less complex. We give some results for the performance measures and compare the proposed bounding models with the exact one. The relevance of our methodology is to offer a trade-off betweencomputational complexity and accuracy of the results and provide very interesting solutions for network dimensioning.
KW - Cloud systems
KW - Performance analysis
KW - Queueing systems
UR - https://www.scopus.com/pages/publications/85010427054
U2 - 10.1109/MASCOTS.2016.38
DO - 10.1109/MASCOTS.2016.38
M3 - Conference contribution
AN - SCOPUS:85010427054
T3 - Proceedings - 2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2016
SP - 319
EP - 324
BT - Proceedings - 2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2016
Y2 - 19 September 2016 through 21 September 2016
ER -