|Table of Contents|

[1] Zhao Guosheng, Ren Mengqi, Wang Jian, Liao Yiwei, et al. Modeling and analysis of cloud computing system survivabilitybased on Bio-PEPA [J]. Journal of Southeast University (English Edition), 2018, (1): 21-27. [doi:10.3969/j.issn.1003-7985.2018.01.004]

Modeling and analysis of cloud computing system survivabilitybased on Bio-PEPA()

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

2018 1
Research Field:
Computer Science and Engineering
Publishing date:


Modeling and analysis of cloud computing system survivabilitybased on Bio-PEPA
Zhao Guosheng1 Ren Mengqi1 Wang Jian2 Liao Yiwei1
1College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China
2School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
cloud computing system Bio-PEPA(biological-performance evaluation process algebra) survivability stochastic simulation
For the cloud computing system, combined with the memory function and incomplete matching of the biological immune system, a formal modeling and analysis method of the cloud computing system survivability is proposed by analyzing the survival situation of critical cloud services. First, on the basis of the SAIR(susceptible, active, infected, recovered)model, the SEIRS(susceptible, exposed, infected, recovered, susceptible)model and the vulnerability diffusion model of the distributed virtual system, the evolution state of the virus is divided into six types, and then the diffusion rules of the virus in the service domain of the cloud computing system and the propagation rules between service domains are analyzed. Finally, on the basis of Bio-PEPA(biological-performance evaluation process algebra), the formalized modeling of the survivability evolution of critical cloud services is made, and the SLIRAS(susceptible, latent, infected, recovered, antidotal, susceptible)model is obtained. Based on the stochastic simulation and the ODEs(ordinary differential equations)simulation of the Bio-PEPA model, the sensitivity parameters of the model are analyzed from three aspects, namely, the virus propagation speed of inter-domain, recovery ability and memory ability. The results show that the proposed model has high approximate fitting degree to the actual cloud computing system, and it can well reflect the survivable change of the system.


[1] Westmark V R. A definition for information system survivability [C]//Proceedings of the 37th Annual Hawaii International Conference on System Science. Washington, DC, USA: IEEE Computer Society, 2004: 2086-2096.DOI:10.1109/HICSS.2004. 1265710.
[2] Mell P, Grance T. The NIST definition of cloud computing[J]. Communications of the ACM, 2011, 53(6): 50-50. DOI: 10.6028/NIST.SP.800-145.
[3] Chang X L, Zhang Z J, Li X D, et al. Model-based survivability analysis of a virtualized system[C]//IEEE 41st Conference on Local Computer Networks(LCN). Dubai, United Arab Emirates, 2016: 611-614. DOI:10.1109/LCN. 2016. 104.
[4] Jin Y L, Zhou X Q, Bai Z S, et al. Survivability-aware topology evolution model with link and node deletion in wireless sensor networks[J]. International Journal of Distributed Sensor Networks, 2014, 10(4): 278629. DOI:10.1155/2014/278629.
[5] Zhou J A, Miao H K, Kai J Y, et al. Survivability prediction of web system based on log statistics[C]//IEEE ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing(SNPD). Takamatsu, Japan, 2015: 15359578. DOI:10.1109/SNPD.2015.7176170.
[6] Alobaidi I A, Sarvestani S S, Hurson A R. Survivability analysis and recovery support for smart grids[C]// 2016 Resilience Week(RWS). Chicago, IL, USA, 2016:33-39. DOI:10.1109/rweek.2016.7573303.
[7] Moldovan R D, Todoran E N. Immune system modeling and analysis using Bio-PEPA[C]//IEEE International Conference on Intelligent Computer Communication and Processing. Cluj-Napoca, Romania, 2015: 475-482. DOI:10.1109/iccp.2015.7312706.
[8] Tan Y, Zhang P. Immune based computer virus detection approaches[J]. CAAI Transactions on Intelligent System, 2013, 8(1): 80-94. DOI:10.3969/j.issn.1673-4785.201209059.
[9] Piqueira J R C, de Vasconcelos A A, Gabriel C E C J, et al. Dynamic models for computer viruses[J]. Computers & Security, 2008, 27(7): 355-359. DOI:10.1016/j.cose.2008.07.006.
[10] Li J, Yang Y, Zhou Y. Global stability of an epidemic model with latent stage and vaccination[J]. Nonlinear Analysis: Real World Applications, 2011, 12(4): 2163-2173. DOI:10.1016/j.nonrwa.2010.12.030.
[11] Lü H W, Wang H Q, Lin J Y, et al. A vulnerability propagation model of distributed virtualized systems based on Bio-PEPA[J]. Chinese Journal of Computers, 2016, 39(2): 391-404. DOI:10.11897/SP.J.1016.2016.00391. (in Chinese)
[12] Ciocchetta F, Hillston J. Bio-PEPA: A framework for the modelling and analysis of biological systems[J].Theoretical Computer Science, 2009, 410(33): 3065-3084. DOI:10.1016/j.tcs.2009.02.037.
[13] Galpin V. Hybrid semantics for Bio-PEPA[J]. Information and Computation, 2014, 236: 122-145. DOI:10.1016/j.ic.2014.01.016.
[14] Duguid A. An overview of the Bio-PEPA eclipse plug-in[C]//Eighth Workshop on Process Algebra and Stochastically Time Activities. Edinburgh, UK, 2009: 121-132.
[15] Zhao J, Zhou Y, Shuo L. A situation awareness model of system survivability based on variable fuzzy set[J]. Indonesian Journal of Electrical Engineering and Computer Science, 2012, 10(8): 2239-2246. DOI:10.11591/telkomnika.v10i8.1691.
[16] Chen T P, Cui W Y, Meng X R, et al. A method of IP network survivability evaluation method under performance monitoring[J]. Journal of Beijing University of Posts and Telecommunications, 2015, 38(6):20-23. DOI:10. 13190/j.jbupt.2015. 06.005. (in Chinese)
[17] Van Mieghem P, Omic J, Kooij R. Virus spread in networks[J]. IEEE/ACM Transactions on Networking, 2009, 17(1): 1-14. DOI:10.1109/tnet.2008.925623.
[18] Gillespie D T. Stochastic simulation of chemical kinetics[J]. Annual Review of Physical Chemistry, 2007, 58(1): 35-55. DOI:10.1146/annurev.physchem.58.032806.104637.


Biography: Zhao Guosheng(1977—), male, doctor, professor, zgswj@163.com.
Foundation items: The National Natural Science Foundation of China(No.61202458, 61403109), the Natural Science Foundation of Heilongjiang Province of China(No.F2017021), Harbin Science and Technology Innovation Research Funds(No.2016RAQXJ036).
Citation: Zhao Guosheng, Ren Mengqi, Wang Jian, et al. Modeling and analysis of cloud computing system survivability based on Bio-PEPA[J].Journal of Southeast University(English Edition), 2018, 34(1):21-27.DOI:10.3969/j.issn.1003-7985.2018.01.004.
Last Update: 2018-03-20