CHALLENGES OF RESOURCE DISCOVERY TO SUPPORT DISTRIBUTED EXASCALE COMPUTING ENVIRONMENT
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Volume 1 (2), December 2018, Pages 168-178
Elham Adibi, Ehsan Mousavi Khaneghah
The resource discovery management unit (RD) in distributed Exascale systems needs to be able to manage the occurrence of dynamic and interactive events in the requesting process when running activities related to RD. The occurrence of dynamic and interactive events in the requesting process causes some challenges in the execution trend of activities related to RD. The trend of execution activities related to RD will fail if there is no management and control on the occurrence of dynamic and interactive events. This paper first explores and describes the concept of dynamic and interactive nature in distributed Exascale systems. In addition, it attempts to show the influences of occurrence the dynamic and interactive events in the computing elements requesting the resource as well as on RD functionality. In addition, this paper aims at describing the challenges of RD to be used in distributed Exascale systems. To achieve this, changes need to be made in the generating space and RD functionality. Taking into account the solutions presented in this paper, RD has the potential to be used in distributed Exascale systems by remaining compatible with traditional computing systems.
exascale computing, resource discovery, dynamic and interactive nature.
 Barak, A., La’adan, O., & Shiloh, A. (1999). Scalable cluster computing with MOSIX for Linux. Proc. 5-th Annual Linux Expo, 100.
 Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., & Wilkes, J. (2015, April). Large-scale cluster management at Google with Borg. In Proceedings of the Tenth European Conference on Computer Systems (p. 18). ACM.
 Reed, D. A., & Dongarra, J. (2015). Exascale computing and big data. Communications of the ACM, 58(7), 56-68.
 Khaneghah, E. M. (2017). U.S. Patent No. 9,613,312. Washington, DC: U.S. Patent and Trademark Office.
 Zarrin, J., Aguiar, R. L., & Barraca, J. P. (2018). Resource discovery for distributed computing systems: A comprehensive survey. Journal of Parallel and Distributed Computing, 113, 127-166.
 Ghebleh, R., & Ghaffari, A. (2017). A Multi-criteria Method for Resource Discovery in Distributed Systems Using Deductive Fuzzy System. International Journal of Fuzzy Systems, 19(6), 1829-1839.
 Arab, M. N., Mirtaheri, S. L., Khaneghah, E. M., Sharifi, M., & Mohammadkhani, M. (2011, September). Improving learning-based request forwarding in resource discovery through load-awareness. In International Conference on Data Management in Grid and P2P Systems (pp. 73-82). Springer, Berlin, Heidelberg.
 Khaneghah, E. M., ShowkatAbad, A. R., & Ghahroodi, R. N. (2018, February). Challenges of Process Migration to Support Distributed Exascale Computing Environment. In Proceedings of the 2018 7th International Conference on Software and Computer Applications (pp. 20-24). ACM.
 Mousavi Khaneghah, E., Mirtaheri, S. L., Sharifi, M., & Minaei Bidgoli, B. (2014). Modeling and analysis of access transparency and scalability in P2P distributed systems. International Journal of Communication Systems, 27(10), 2190-2214.
 Silberschatz, A., Galvin, P. B., & Gagne, G. (2014). Operating system concepts essentials. John Wiley & Sons, Inc..
 Brömmel, D., Suarez, E., Orth, B., Graf, S., Detert, U., Pleiter, D., ... & Lippert, T. (2014). Paving the road towards pre-Exascale supercomputing. In NIC Symposium 2014 (No. FZJ-2014-01327). Jülich Supercomputing Center.
 Mallon, A. D., Lippert, T., Beltran, V., Affinito, F., Jaure, S., Merx, H., ... & Eicker, N. (2013). Programming model and application porting to the Dynamical Exascale Entry Platform (DEEP). In Proceedings of the Exascale Applications and Software Conference, Edinburgh, Scotland, UK.
 Pouya, I., Pronk, S., Lundborg, M., & Lindahl, E. (2017). Copernicus, a hybrid dataflow and peer-to-peer scientific computing platform for efficient large-scale ensemble sampling. Future Generation Computer Systems, 71, 18-31.
 Kaur, K., & Rai, A. K. (2014). A comparative analysis: Grid, cluster and cloud computing. International Journal of Advanced Research in Computer and Communication Engineering, 3(3), 5730-5734.
 Khaneghah, E. M., & Sharifi, M. (2014). AMRC: an algebraic model for reconfiguration of high performance cluster computing systems at runtime. The Journal of Supercomputing, 67(1), 1-30.
 Khaneghah, E. M., & Ghoreishi, S. A. (2017, June). CGUW: A system software for heterogeneous IPC mechanism in grid computing environments. In 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 58-62). IEEE.
 Navimipour, N. J., & Milani, F. S. (2015). A comprehensive study of the resource discovery techniques in peer-to-peer networks. Peer-to-Peer Networking and Applications, 8(3), 474-492.
 Qureshi, M. B., Dehnavi, M. M., Min-Allah, N., Qureshi, M. S., Hussain, H., Rentifis, I., ... & Zomaya, A. Y. (2014). Survey on grid resource allocation mechanisms. Journal of Grid Computing, 12(2), 399-441.
 Kaur, M., & Kadam, S. S. (2017). Discovery of resources using MADM approaches for parallel and distributed computing. International Journal Engineering science and technology, 20(3), 1013-1024.
 Mirtaheri, S. L., & Sharifi, M. (2014). An efficient resource discovery framework for pure unstructured peer-to-peer systems. Computer Networks, 59, 213-226.
 Kashyian, M., Mirtaheri, S. L., & Khaneghah, E. M. (2008, September). Portable inter process communication programming. In The Second International Conference on Advanced Engineering Computing and Applications in Sciences, 2008. ADVCOMP’08 (pp. 181-186). IEEE.
 Sharifi, M., Mirtaheri, S. L., & Khaneghah, E. M. (2010). A dynamic framework for integrated management of all types of resources in P2P systems. The Journal of Supercomputing, 52(2), 149-170.
 Wu, J. (2017). Distributed system design. CRC press.
 Bisbee, S. F., Moskowitz, J. J., Becker, K. F., Peterson, E. K., & Twaddell, G. W. (2017). U.S. Patent Application No. 13/369,112.
 Mousavi Khaneghah, E., Noorabad Ghahroodi, R., & Reyhani ShowkatAbad, A. (2018). A mathematical multi-dimensional mechanism to improve process migration efficiency in peer-to-peer computing environments. Cogent Engineering, 5(1), 1458434.
 Hesselink, L., Rizal, D., & Bjornson, E. S. (2015). U.S. Patent No. 9,191,443. Washington, DC: U.S. Patent and Trademark Office.