Secure-Sim-G: Security-Aware Grid Simulator – Basic Concept and Structure
DOI:
https://doi.org/10.26636/jtit.2012.1.1250Keywords:
computational grid, grid simulator, scheduling, securityAbstract
Task scheduling and resource allocation are the key issues for computational grids. Distributed resources usually work at different autonomous domains with their own access and security policies that impact successful job executions across the domain boundaries. In this paper we present a security-aware grid simulator Secure-Sim-G, which facilitates the evaluation of the different scheduling heuristics under various scheduling criteria in several grid scenarios defined by the security conditions, grid size and system dynamics. The simulator allows the flexible activation or inactivation of all of the scheduling criteria and modules, which makes the application well adapted to the proper illustration of the different realistic scenarios and avoids the possible restriction to the specific scheduling resolution methods. The simulation results and traces may be graphically represented and stored at the server and can retrieved in different formats such as spreadsheets or pdf files.
Downloads
References
[1] F. Xhafa, J. Carretero, L. Barolli, and A. Durresi, „Requirements for an event-based simulation package for grid systems”, J. Interconnection Netw., vol. 8, no. 2, pp. 163-178, 2007.
View in Google Scholar
[2] H. J. Song et al., „The microgrid: a scientific tool for modeling computational grids”, J. Sci. Program., vol. 8, no. 3, pp. 127-141, 2000.
View in Google Scholar
[3] K. Ranganathan and I. Foster, „Simulation studies of computation and data scheduling algorithms for data grids”, J. Grid Comput., vol. 1, no. 1, pp. 53-62, 2003.
View in Google Scholar
[4] R. Buyya and M. M. Murshed, „Grid-Sim: a toolkit for the modeling and simulation of distributed resource management and scheduling for grid computing”, Concurrency Comput.: Pract. Exper., vol. 14, no. 13-15, pp. 1175-1220, 2002.
View in Google Scholar
[5] O. Kang and S. Kang, „Web-based dynamic scheduling platform for grid computing”, Int. J. Comput. Sci. Netw. Secur., vol. 6, no. 5, pp. 67-75, 2006.
View in Google Scholar
[6] S. Song, K. Hwang, and Y. K. Kwok, „Risk-resilient heuristics and genetic algorithms for security-assured grid job scheduling”, IEEE Trans. Comput., vol. 55, no. 6, pp. 703-719, 2006.
View in Google Scholar
[7] S. Song, K. Hwang, and Y. K. Kwok, „Trusted grid computing with security binding and trust integration”, J. Grid Comput., vol. 3, no. 1-2, pp. 53-73, 2005.
View in Google Scholar
[8] M. Humphrey and M. R. Thompson, „Security implications of typical grid computing usage scenarios”, in Proc. 10th IEEE Int. Symp. High Perform. Distrib. Comput., San Francisco, CA, USA, 2001.
View in Google Scholar
[9] E. Cody, R. Sharman, R. H. Rao, and S. Upadhyaya, „Security in grid computing: a review and synthesis”, Decis. Support Syst., vol. 44, pp. 749-764, 2008.
View in Google Scholar
[10] S. Hwang and C. Kesselman, „A flexible framework for fault tolerance in the grid”, J. Grid Comput., vol. 1, no. 3, pp. 251-272, 2003.
View in Google Scholar
[11] J. Abawajy, „An efficient adaptive scheduling policy for high performance computing”, Future Gener. Comput. Syst., vol. 25, no. 3, pp. 364-370, 2009.
View in Google Scholar
[12] J. Kołodziej and F. Xhafa, „Meeting security and user behaviour requirements in grid scheduling”, Simul. Model. Pract. Theory, vol. 19, no. 1, pp. 213-226, 2011.
View in Google Scholar
[13] J. Kołodziej, F. Xhafa, and M. Bogdański, „Secure and task abortion aware ga-based hybrid metaheuristics for grid scheduling”, in Parallel Problem Solving from Nature - PPSN XI, R. Schaefer et al., Eds., LNCS, vol. 6238. Springer, 2010, pp. 526-535.
View in Google Scholar
[14] J. Kołodziej and F. Xhafa, „Integration of Task Abortion and Security Requirements in GA-based Meta-Heuristics for Independent Batch Grid Scheduling”, Comput. Math. Appl., DOI: 10.1016/j.camwa.2011.07.038, 2011.
View in Google Scholar
[15] J. Kołodziej and F. Xhafa, „A game-theoretic and hybrid genetic meta-heuristic model for security-assured scheduling of independent jobs in computational grids”, in Proc. CISIS 2010, USA: IEEE Press, 2010, pp. 93-100.
View in Google Scholar
[16] S. Ali, H. J. Siegel, M. Maheswaran, and D. Hensgen, „Task execution time modeling for heterogeneous computing systems”, in Proc. 9th Heterogen. Comput. Worksh. HCW 2000, Cancun, Mexico, 2000, pp. 185-199.
View in Google Scholar
[17] F. Xhafa, J. Carretero, E. Alba, and B. Dorronsoro, „Tabu search algorithm for scheduling independent jobs in computational grids”, Comput. Inform. J., special issue on Intelligent Computational Methods, J. Burguillo-Rial, J. Kołodziej, and L. Nolle, Eds., vol. 28, no. 2, pp. 237-249, 2009.
View in Google Scholar
[18] F. Xhafa and A. Abraham, „Meta-heuristics for grid scheduling problems”, in Meta-heuristics for Scheduling in Distributed Computing Environments, Chapter 1, Series Studies in Computational Intelligence, Springer, 2009, pp. 1-37.
View in Google Scholar
[19] F. Xhafa, J. Carretero, and A. Abraham, „Genetic algorithm based schedulers for grid computing systems”, Int. J. Innovative Comput. Inform. Control, vol. 3, no. 5, pp. 1053-1071, 2007.
View in Google Scholar
[20] F. Pinel, J. E. Pecero, P. Bouvry, and S. U. Khan, „A two-phase heuristic for the scheduling of independent tasks on computational grids”, in Proc. ACM/IEEE/IFIP Int. Conf. High Perform. Comput. Simul. HPCS 2011, Istanbul, Turkey, 2011.
View in Google Scholar
[21] J. Kołodziej, F. Xhafa, and Ł. Kolanko, „Hierarchic genetic scheduler of independent jobs in computational grid environment”, in Proc. 23rd Eur. Conf. Model. Simul. ECMS 2009, Madrid, Spain, 2009, J. Otamendi, A. Bargieła, J. L. Montes and L. M. Doncel Pedrera, Eds. Dudweiler, Germany: IEEE Press, 2009, pp. 108-115.
View in Google Scholar
[22] J. Kołodziej and F. Xhafa, „Enhancing the genetic-based scheduling in computational grids by a structured hierarchical population”, Future Gener. Comput. Syst., vol. 27, pp. 1035-1046, 2011, DOI: 10.1016/j.future.2011.04.011.
View in Google Scholar
[23] F. Xhafa, J. Carretero, and A. Abraham, „Genetic algorithm based schedulers for grid computing systems”, Int. J. Innovative Comput. Inform. Control, vol. 3, no. 5, pp. 1053-1071, 2007.
View in Google Scholar
[24] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. Springer, 1992.
View in Google Scholar
[25] J. Kołodziej, S. U. Khan, and F. Xhafa, „Genetic algorithms for energy-aware scheduling in computational grids”, in Proc. 6th IEEE Int. Conf. P2P, Parallel, Grid, Cloud, Internet Comput. 3PGCIC, Barcelona, Spain, 2011.
View in Google Scholar
[26] D. Kliazovich, P. Bouvry, Y. Audzevich, and S. U. Khan, „GreenCloud: a packet-level simulator of energy-aware cloud computing data centers”, in Proc. 53rd IEEE Global Commun. Conf. Globecom 2010, Miami, FL, USA, 2010.
View in Google Scholar
[27] S. U. Khan and I. Ahmad, „A cooperative game theoretical technique for joint optimization of energy consumption and response time in computational grids”, IEEE Trans. Parallel and Distrib. Sys., vol. 20, no. 3, pp. 346-360, 2009.
View in Google Scholar
[28] S. U. Khan, „A goal programming approach for the joint optimization of energy consumption and response time in computational grids”, in Proc. 28th IEEE Int. Perform. Comput. Commun. Conf. IPCCC 2009, Phoenix, AZ, USA, 2009, pp. 410-417.
View in Google Scholar
[29] S. U. Khan and I. Ahmad, „Non-cooperative, semi-cooperative, and cooperative games-based grid resource allocation”, in Proc. 20th IEEE Int. Parallel Distrib. Process. Symp. IPDPS 2006, Rhodes Island, Greece, 2006.
View in Google Scholar
[30] G. L. Valentini et al., „An overview of energy efficiency techniques in cluster computing systems”, Cluster Comput., DOI: 10.1007/s10586-011-0171-x, 2011.
View in Google Scholar
[31] L. Wang and S. U. Khan, „Review of performance metrics for green data centers: a taxonomy study”, J. Supercomput., pp. 1-18, 2011, DOI: 10.1007/s11227-011-0704-3.
View in Google Scholar
[32] S. Zeadally, S. U. Khan, and N. Chilamkurti, „Energy-efficient networking: past, present, and future”, J. Supercomput., pp. 1-26, 2011, DOI: 10.1007/s11227-011-0632-2.
View in Google Scholar
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2012 Journal of Telecommunications and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
