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Energy Conserving Secure VM Allocation in Untrusted Cloud Computing Environment

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Published:16 November 2017Publication History

ABSTRACT

Cloud computing is the latest buzz in most of the IT organizations which are witnessing a a trend of migration from traditional computing to cloud computing, thereby reducing their infrastructure cost and improving efficiency and performance. Cloud computing provides services through virtualization layer, which helps to execute more than one operating systems and applications on a single machine. Being a crucial part of cloud computing, virtualization layer faces major security threats, most challenging being an insider threat wherein attacker can either compromise existing virtual machines (VMs) or create rogue VMs. The objective of this work is to propose virtual machine (VM) allocation algorithm which operates in an untrusted cloud computing environment with non-trustworthy VMs. Our approach is based on the notion of trust. Lack of trust is modeled by either introducing faults or monitoring SLAs per host on which VMs are hosted. Detailed experiments considering varying cloud infrastructure and varying workloads are conducted using CloudSim. Results show that proposed algorithm works well in untrusted environment while at the same time is energy efficient and reduces the computational costs by decreasing the number of migrations and SLA violations.

References

  1. Robin J Adair, RJ Creasey, RU Bayles, and LW Comeau. 1966. A virtual machine system for the 360/40. Technical Report.Google ScholarGoogle Scholar
  2. Mohammed Alhamad, Tharam Dillon, and Elizabeth Chang. 2010. Sla-based trust model for cloud computing. In Network-Based Information Systems (NBiS), 2010 13th International Conference on. IEEE, 321--324. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Florina Almenárez, Andrés Marín, Celeste Campo, and Carlos Garcia. 2004. PTM: A pervasive trust management model for dynamic open environments. In First Workshop on Pervasive Security, Privacy and Trust PSPT, Vol. 4. 1--8.Google ScholarGoogle Scholar
  4. Anton Beloglazov. 2013. Energy-efficient management of virtual machines in data centers for cloud computing. University of Melbourne, Department of Computing and Information Systems.Google ScholarGoogle Scholar
  5. Anton Beloglazov, Jemal Abawajy, and Rajkumar Buyya. 2012. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future generation computer systems 28, 5 (2012), 755--768. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Anton Beloglazov and Rajkumar Buyya. 2012. Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers. Concurrency and Computation: Practice and Experience 24, 13 (2012), 1397--1420. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Rodrigo N Calheiros, Rajiv Ranjan, Anton Beloglazov, César AF De Rose, and Rajkumar Buyya. 2011. CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and experience 41, 1 (2011), 23--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. William R Claycomb and Alex Nicoll. 2012. Insider threats to cloud computing: Directions for new research challenges. In Computer Software and Applications Conference (COMPSAC), 2012 IEEE 36th Annual. IEEE, 387--394. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Wesam Dawoud, Ibrahim Takouna, and Christoph Meinel. 2010. Infrastructure as a service security: Challenges and solutions. In Informatics and Systems (INFOS), 2010 the 7th International Conference on. IEEE, 1--8.Google ScholarGoogle Scholar
  10. R Kanniga Devi and S Sujan. 2014. A survey on application of cloudsim toolkit in cloud computing. International Journal of Innovative Research in Science, Engineering and Technology 3, 6 (2014), 13146--13153.Google ScholarGoogle Scholar
  11. Nils Gruschka and Meiko Jensen. 2010. Attack surfaces: A taxonomy for attacks on cloud services. In Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on. IEEE, 276--279. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Punit Gupta, Mayank Kumar Goyal, and Prakash Kumar. 2013. Trust and reliability based load balancing algorithm for cloud IaaS. In Advance Computing Conference (IACC), 2013 IEEE 3rd International. IEEE, 65--69.Google ScholarGoogle ScholarCross RefCross Ref
  13. Yi Han, Jeffrey Chan, Tansu Alpcan, and Christopher Leckie. 2014. Virtual machine allocation policies against co-resident attacks in cloud computing. In Communications (ICC), 2014 IEEE International Conference on. IEEE, 786--792.Google ScholarGoogle ScholarCross RefCross Ref
  14. Miltiadis Kandias, Nikos Virvilis, and Dimitris Gritzalis. 2011. The insider threat in cloud computing. In International Workshop on Critical Information Infrastructures Security. Springer, 93--103.Google ScholarGoogle Scholar
  15. Ryan KL Ko, Peter Jagadpramana, Miranda Mowbray, Siani Pearson, Markus Kirchberg, Qianhui Liang, and Bu Sung Lee. 2011. TrustCloud: A framework for accountability and trust in cloud computing. In Services (SERVICES), 2011 IEEE World Congress on. IEEE, 584--588. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Shengmei Luo, Zhaoji Lin, Xiaohua Chen, Zhuolin Yang, and Jianyong Chen. 2011. Virtualization security for cloud computing service. In Cloud and Service Computing (CSC), 2011 International Conference on. IEEE, 174--179. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Mihaela-Catalina Nita, Florin Pop, Mariana Mocanu, and Valentin Cristea. 2014. FIM-SIM: Fault injection module for CloudSim based on statistical distributions. Journal of telecommunications and information technology 4 (2014), 14.Google ScholarGoogle Scholar
  18. Jon Oberheide, Evan Cooke, and Farnam Jahanian. 2008. Empirical exploitation of live virtual machine migration. In Proc. of BlackHat DC convention.Google ScholarGoogle Scholar
  19. Mendel Rosenblum. 2004. The reincarnation of virtual machines. Queue 2, 5 (2004), 34. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Xiaodong Sun, Guiran Chang, and Fengyun Li. 2011. A trust management model to enhance security of cloud computing environments. In Networking and Distributed Computing (ICNDC), 2011 Second International Conference on. IEEE, 244--248. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Yan Lindsay Sun, Wei Yu, Zhu Han, and KJ Ray Liu. 2006. Information theoretic framework of trust modeling and evaluation for ad hoc networks. IEEE Journal on Selected Areas in Communications 24, 2 (2006), 305--317. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Chia-Ming Wu, Ruay-Shiung Chang, and Hsin-Yu Chan. 2014. A green energy-efficient scheduling algorithm using the DVFS technique for cloud datacenters. Future Generation Computer Systems 37 (2014), 141--147.Google ScholarGoogle ScholarCross RefCross Ref
  23. Munwar Ali Zardari, Low Tang Jung, and Nordin Zakaria. 2014. K-NN classifier for data confidentiality in cloud computing. In Computer and Information Sciences (ICCOINS), 2014 International Conference on. IEEE, 1--6.Google ScholarGoogle ScholarCross RefCross Ref

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      cover image ACM Other conferences
      Compute '17: Proceedings of the 10th Annual ACM India Compute Conference
      November 2017
      148 pages
      ISBN:9781450353236
      DOI:10.1145/3140107

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      Publication History

      • Published: 16 November 2017

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      Compute '17 Paper Acceptance Rate19of70submissions,27%Overall Acceptance Rate114of622submissions,18%
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