Abstract
Virtualization allows integrating Field Programmable Gate Arrays (FPGAs) into a resource pool at the infra-structure layer. So as to improve the FPGA resource utilization while ensuring the quality of service, a virtual FPGA (vFPGA) Scheduling algorithm has been presented in our early work. At the meantime, we noticed that the initial deployment of vFPGAs has obvious effect on resource utilization ratio. Finding an optimal deployment of vFPGAs onto FPGAs which can be summed up in virtual FPGA placement (VFP) problem is a NP-hard problem. With a widespread of reconfigurable cryptographic resource pool, regarded it as a combinatorial optimization problem have offered higher efficiency than linear programming (LP) problem. In this paper, an optimized ant colony optimization (ACO) algorithm, where given ants the ability to perceive resource status, is presented to achieve the VFP goal. Finally, CloudSim toolkit is extended to evaluate our solution through simulations on synthetic workloads. The obtained results show that our algorithm can reduce the number of active FPGAs by improving the resource utilization.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Amazon Web Services. AWS CloudHSM User Guide. https://docs.aws.amazon.com/cloudhsm/latest/userguide/cloudhsm-user-guide.pdf. Accessed 23 Apr 2019
QI, K.: The first Cloud Data Encryption Service released by Alibaba Cloud and JN TASS. Inf. Secur. Commun. Priv. (1), 87 (2016)
Vipin, K., Fahmy, S.A.: FPGA dynamic and partial reconfiguration: a survey of architectures, methods, and applications. ACM Comput. Surv. (CSUR) 51(4), 72 (2018)
Xu, Y., Sun, L., Guo, S., et al.: Research and design of reconfigurable security resource pool framework. In: Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence, pp. 620–626. ACM, Shenzhen (2018)
Calheiros, R.N., Ranjan, R., Beloglazov, A., et al.: CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw.: Pract. Exp. 41(1), 23–50 (2011)
Speitkamp, B., Bichler, M.: A mathematical programming approach for server consolidation problems in virtualized data centers. IEEE Trans. Serv. Comput. 3(4), 266–278 (2010)
Teyeb, H., Balma, A., Hadj-Alouane, N.B., Tata, S.: Optimal virtual machine placement in a multi-tenant cloud. In: Toumani, F., et al. (eds.) ICSOC 2014. LNCS, vol. 8954. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22885-3_27
Dai, X., Wang, M., Bensaou, B.: Energy-efficient virtual machines scheduling in multi-tenant data centers. IEEE Trans. Cloud Comput. 4(2), 210–221 (2016)
Riahi, M., Krichen, S.: A multi-objective decision support framework for virtual machine placement in cloud data centers: a real case study. J. Supercomput. 74, 2984–3015 (2018)
Veredas, F.J., Carmona, E.J.: FPGA placement improvement using a genetic algorithm and the routing algorithm as a cost function. In: 2018 21st Euromicro Conference on Digital System Design (DSD). IEEE (2018)
Haghighi, A.M., Mehrdad, M., et al.: An energy-efficient dynamic resource management approach based on clustering and meta-heuristic algorithms in cloud computing IaaS platforms. Wirel. Pers. Commun. 104(4), 1367–1391 (2019)
Yang, X., Ma, Z., Sun, L.: Research on batch deployment of virtual machines based on improved ant colony algorithm in cloud environment. Comput. Sci. 39(9), 33–37 (2012)
Liu, X.F., et al.: An energy efficient ant colony system for virtual machine placement in cloud computing. IEEE Trans. Evol. Comput. 22(1), 113–128 (2018)
Jing, C., Zhu, Y., Li, M.: Energy-efficient scheduling on multi-FPGA reconfigurable systems. Microprocess. Microsyst. 37(6–7), 590–600 (2013)
Jing, C.: Ant-colony optimization based algorithm for energy-efficient scheduling on dynamically reconfigurable systems. In: Ninth International Conference on Frontier of Computer Science & Technology. IEEE Computer Society (2015)
Fahmy, S.A., Vipin, K., Shreejith, S.: Virtualized FPGA accelerators for efficient cloud computing. In: IEEE, International Conference on Cloud Computing Technology and Science, pp. 430–435. IEEE Computer Society, Dubai, UAE (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Xu, Y., Sun, L., Guo, S., Liu, H. (2020). Virtual FPGA Placement with an Efficient Ant Colony Optimization. In: Han, W., Zhu, L., Yan, F. (eds) Trusted Computing and Information Security. CTCIS 2019. Communications in Computer and Information Science, vol 1149. Springer, Singapore. https://doi.org/10.1007/978-981-15-3418-8_10
Download citation
DOI: https://doi.org/10.1007/978-981-15-3418-8_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3417-1
Online ISBN: 978-981-15-3418-8
eBook Packages: Computer ScienceComputer Science (R0)